<p><strong>Overview</strong></p><p>We are seeking an experienced Data Engineer to join a growing data team supporting enterprise analytics, reporting, and data science initiatives. This role will focus on supporting and enhancing existing data pipelines while contributing to new development efforts within a modern data environment. The ideal candidate will have strong experience with Databricks, SQL, and Python, along with the ability to partner directly with business stakeholders and translate business requirements into scalable technical solutions.</p><p> </p><p><strong>POSITION: DATA ENGINEER</strong></p><p><strong>LOCATION: DALLAS, TX ONSITE</strong></p><p><strong>DURATION: 6-MONTH CONTRACT-TO-HIRE</strong></p><p> </p><p><strong>RESPONSIBILITIES</strong></p><ul><li>Develop, support, and enhance ETL and data pipeline solutions.</li><li>Design and build data transformations across Bronze, Silver, and Gold data layers within a Medallion Architecture environment.</li><li>Write, optimize, and troubleshoot complex SQL queries to support reporting, analytics, and operational business needs.</li><li>Develop and maintain data processing solutions using Python and PySpark within Databricks.</li><li>Partner directly with business stakeholders to gather requirements and translate business needs into technical solutions.</li><li>Monitor, troubleshoot, and resolve data pipeline issues while performing root cause analysis.</li><li>Design and maintain data warehouse and database models that support reporting, analytics, and data science initiatives.</li><li>Deliver trusted and certified datasets that power dashboards, self-service analytics, and business reporting.</li><li>Apply best practices related to data quality, testing, monitoring, performance optimization, documentation, and maintainability.</li><li>Collaborate with data engineers, analysts, data scientists, and business teams on strategic initiatives and ongoing support efforts.</li></ul>
<p>Hybrid schedule out of Seffner, FL office – 3 days in, 2 days WFH</p><p>6 month Contract-To-Permanent (client will be converting this person to a permanent employee at 6 months)</p><p><strong> </strong></p><p><strong>Position Overview</strong></p><p>We are seeking a Data Engineer with deep expertise in Databricks to design, develop, and optimize scalable data solutions. This role will focus heavily on Databricks technologies including Lakeflow Declarative Pipelines, Lakebase, Genie, and AI/BI Dashboards. The ideal candidate will have strong Python and SQL skills, hands-on experience building modern data pipelines, and a proven track record working within the Databricks ecosystem.</p><p><strong> </strong></p><p>This role is ideal for a highly technical Data Engineer who is passionate about the Databricks ecosystem and enjoys building scalable, modern data solutions that drive business value.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design, develop, and support data solutions within the Databricks platform</li><li>Build and optimize Lakeflow Declarative Pipelines for data ingestion and transformation</li><li>Work with Lakebase to support scalable, high-performance data architecture</li><li>Leverage Databricks Genie to enhance data accessibility and business user interactions</li><li>Develop and support AI/BI Dashboards to deliver actionable business insights</li><li>Create, optimize, and maintain complex SQL queries and Python-based data workflows</li><li>Collaborate with business stakeholders, analysts, and engineering teams to deliver data-driven solutions</li><li>Ensure data quality, performance, scalability, and reliability across the data platform</li></ul>
<p><strong>Robert Half</strong> is actively partnering with an Austin-based client to identify a Data Engineer <strong>(contract).</strong> In this role, you will provide both technical and project leadership in designing, developing, and optimizing modern data solutions. This role will partner closely with business and technology stakeholders to deliver scalable data pipelines, drive data strategy initiatives, and lead cross-functional teams in a fast-paced enterprise environment. <strong>This role is hybrid in Austin, Tx. </strong></p><p><br></p><p><strong>Key Responsibilities:</strong></p><ul><li>Lead the design, development, and delivery of enterprise data engineering and integration initiatives.</li><li>Partner with business stakeholders to gather requirements, define solutions, and ensure successful project execution.</li><li>Drive Agile delivery practices while supporting strategic business priorities and innovation initiatives.</li><li>Architect, build, and optimize scalable data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.</li><li>Develop and maintain robust ETL/ELT processes to integrate data from multiple enterprise systems and external sources.</li><li>Implement data quality controls, validation processes, and monitoring frameworks to ensure data accuracy and reliability.</li><li>Mentor and guide junior engineers, fostering technical growth and supporting team success.</li><li>Establish and maintain data security, governance, and access control standards.</li><li>Collaborate with product owners, engineering teams, analysts, QA, operations, and project stakeholders to deliver high-quality solutions.</li><li>Translate business requirements into technical specifications, data mappings, and implementation plans.</li><li>Identify project risks, dependencies, and technical challenges while developing mitigation strategies.</li><li>Create and maintain documentation for deployments, support procedures, and operational processes.</li><li>Support deployment automation, application support efforts, and continuous process improvement initiatives.</li><li>Coordinate with distributed teams across multiple locations and time zones to drive successful project outcomes.</li></ul>
<p><strong>Data Engineer</strong></p><p><br></p><p><strong>Company Overview</strong></p><p>A leading food manufacturing and distribution organization is seeking a Data Engineer to support enterprise data initiatives and drive business intelligence capabilities. Based in Los Angeles, California, the company serves a large network of customers through innovative operations, quality-focused processes, and data-driven decision making. This is an opportunity to join a collaborative team where technology and analytics play a critical role in business growth and operational excellence.</p><p><br></p><p><strong>Role Summary</strong></p><p>The Data Engineer will be responsible for designing, building, and maintaining scalable data pipelines that support reporting, analytics, and business operations. This role will partner closely with analysts and cross-functional stakeholders to transform raw data into reliable, actionable insights. The ideal candidate brings experience in manufacturing or food production environments and possesses strong expertise in data warehousing, ETL development, cloud technologies, and reporting platforms.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design, develop, and maintain scalable ETL and ELT data pipelines.</li><li>Build and optimize data workflows that consolidate information from multiple business systems.</li><li>Partner with business stakeholders and analysts to translate data requirements into technical solutions.</li><li>Develop and maintain data models and warehouse structures to support reporting and analytics.</li><li>Monitor, troubleshoot, and enhance data pipelines to ensure data accuracy, integrity, and availability.</li><li>Optimize data storage and retrieval processes for performance, scalability, and reliability.</li><li>Support business intelligence initiatives by delivering clean, trusted datasets for reporting and dashboards.</li><li>Create and maintain technical documentation for data architecture, processes, and workflows.</li><li>Collaborate with engineering, analytics, and business teams to drive data-driven decision making.</li><li>Stay current on emerging technologies and best practices in data engineering and analytics.</li></ul><p><strong>Additional Details</strong></p><ul><li>Work model: On-site for the first 90 days, transitioning to a hybrid schedule thereafter</li><li>Join a team of analytics professionals supporting enterprise reporting and data initiatives</li><li>Opportunity to have a direct impact on operational and business performance through data solutions</li></ul>
<p><strong>Senior Data Engineer (Contract)</strong></p><p><strong>Location:</strong> Glendale, CA | Hybrid</p><p><strong>Employment Type:</strong> Long Term Contract</p><p><strong>Pay: </strong>Available on W2 Basis</p><p><strong>Position Overview</strong></p><p>We are seeking a <strong>Senior Data Engineer</strong> to support enterprise data engineering and platform modernization initiatives. This role will focus on designing, building, and optimizing scalable data solutions while partnering with cross-functional teams to enhance cloud-based data platforms and data-driven decision-making.</p><p>The ideal candidate will bring strong expertise in <strong>Databricks, Python, Apache Spark, and Terraform</strong>, along with experience designing and operating enterprise-scale data pipelines and platforms. This position offers the opportunity to work on complex data engineering challenges involving modern cloud technologies, streaming and batch processing, automation, governance, and platform architecture.</p><p><strong>Key Responsibilities</strong></p><ul><li>Design, develop, test, deploy, and maintain scalable batch and streaming data pipelines.</li><li>Build and optimize data solutions using Databricks, Apache Spark, Python, SQL, and related technologies.</li><li>Collaborate with stakeholders to gather requirements and translate business needs into scalable technical solutions.</li><li>Support and maintain data platform governance, including access controls, data lineage, cataloging, and data discovery capabilities.</li><li>Diagnose platform and pipeline issues, identify root causes, and recommend effective solutions.</li><li>Contribute to solution architecture across cloud, data, and orchestration platforms.</li><li>Develop and maintain containerized services and utilities using Docker and Kubernetes.</li><li>Implement infrastructure automation and deployment standards using Infrastructure as Code practices.</li><li>Monitor platform health, resource utilization, system performance, and operational efficiency.</li><li>Build and enhance CI/CD processes and DevOps workflows.</li><li>Implement data quality, monitoring, logging, and reliability standards across pipelines and platforms.</li><li>Partner with engineers, architects, product teams, and business stakeholders in an Agile environment.</li><li>Maintain technical documentation, standards, and platform configurations</li></ul>
<p>Robert Half is seeking an experienced <strong>Senior Data Engineer</strong> to support a <strong>law firm based in Seattle, Washington</strong> with the continued development and modernization of its enterprise data environment. This role will focus heavily on <strong>Databricks, dimensional modeling, PySpark, and Unity Catalog</strong>, with responsibility for ingesting, transforming, and preparing data from multiple enterprise systems for reporting and analytics.</p><p> </p><p><strong>Duration:</strong> 6-month contract</p><p><strong>Location:</strong> 100% Remote – preferred to work PST or CST</p><p><strong>Pay rate: </strong>$65-$75/hour (W2)</p><p> </p><p><strong>Responsibilities</strong></p><ul><li>Design, develop, and maintain scalable data pipelines and data models within <strong>Databricks</strong>.</li><li>Build and optimize <strong>dimensional data models</strong> to support enterprise reporting and analytics.</li><li>Develop data transformation and processing workflows using <strong>PySpark</strong>.</li><li>Ingest data from enterprise source systems, including <strong>Workday, Elite/Elite 3E, and Salesforce</strong>.</li><li>Move data through the <strong>Medallion Architecture</strong>, including Bronze, Silver, and Gold layers.</li><li>Clean, normalize, transform, and prepare source data for downstream analytics and reporting.</li><li>Utilize <strong>Unity Catalog</strong> to support data governance, security, organization, and access management.</li><li>Prepare curated datasets for consumption and reporting within <strong>Power BI</strong>.</li><li>Partner with business and technical stakeholders to understand reporting needs and demonstrate data within Power BI.</li><li>Troubleshoot data connectivity and integration issues involving <strong>APIs, Postman, firewall rules, and certificates</strong>.</li><li>Ensure data pipelines and models are scalable, reliable, and aligned with data engineering best practices.</li></ul>
<p>Robert Half is seeking a <strong>Contract Data Engineer</strong> to support our client’s data and analytics initiatives. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure that enable efficient data ingestion, transformation, and delivery. The ideal candidate has strong experience working with modern data platforms, cloud environments, and large-scale datasets.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><ul><li><strong>Data Pipeline Development:</strong> Design, build, and maintain scalable ETL / ELT pipelines to ingest, transform, and deliver data from multiple sources.</li><li><strong>Data Architecture:</strong> Develop and optimize data models, schemas, and warehouse structures to support analytics, reporting, and business intelligence needs.</li><li><strong>Cloud Data Platforms:</strong> Work within cloud environments such as <strong>AWS, Azure, or GCP</strong> to deploy and manage data solutions.</li><li><strong>Data Warehousing:</strong> Design and support enterprise data warehouses using platforms such as <strong>Snowflake, Redshift, BigQuery, or Azure Synapse</strong>.</li><li><strong>Big Data Processing:</strong> Develop solutions using big data technologies such as <strong>Spark, Databricks, Kafka, and Hadoop</strong> when required.</li><li><strong>Performance Optimization:</strong> Tune queries, pipelines, and storage solutions for performance, scalability, and cost efficiency.</li><li><strong>Data Quality & Reliability:</strong> Implement monitoring, validation, and alerting processes to ensure data accuracy, integrity, and availability.</li><li><strong>Collaboration:</strong> Work closely with Data Analysts, Data Scientists, Software Engineers, and business stakeholders to understand requirements and deliver data solutions.</li><li><strong>Documentation:</strong> Maintain detailed documentation for pipelines, data flows, and system architecture.</li></ul><p><br></p>
<p>We are looking for an experienced Data Engineer for a full time opportunity in Northern, Virginia. In this role, you will design reliable data solutions that support analytics and business decision-making while helping improve the overall data environment. The ideal candidate brings strong technical depth in modern data engineering practices and enjoys building scalable systems from the ground up.</p><p><br></p><p>Responsibilities:</p><p>• Design, develop, and maintain robust data pipelines that collect, transform, and deliver high-quality data for reporting and analysis.</p><p>• Create and optimize data models that support business intelligence, analytics, and operational use cases across the organization.</p><p>• Build and manage ETL workflows using Python and related technologies to ensure efficient movement of data between systems.</p><p>• Work with large-scale data processing tools such as Apache Spark and Hadoop to handle complex and high-volume datasets.</p><p>• Integrate streaming and batch data sources using technologies such as Apache Kafka to support timely and reliable data availability.</p><p>• Collaborate with analysts, engineers, and business stakeholders to translate data needs into scalable engineering solutions.</p><p>• Improve data warehouse performance, structure, and reliability to support accurate and accessible enterprise data.</p><p>• Use dbt and other modern data transformation practices to organize, test, and document datasets effectively.</p>
We are looking for a Data Engineer to support scalable data solutions for a long-term contract opportunity in The Woodlands, Texas. This role focuses on designing and optimizing data pipelines, integrating large-scale data sources, and enabling reliable access to critical business information. The ideal candidate will bring strong hands-on experience with modern big data technologies and a practical approach to building efficient ETL workflows.<br><br>Responsibilities:<br>• Build, maintain, and enhance robust data pipelines to process large volumes of structured and unstructured information.<br>• Develop ETL workflows that transform raw data into reliable datasets for analytics, reporting, and operational use.<br>• Use Python and Apache Spark to engineer high-performance data processing solutions across distributed environments.<br>• Work with Apache Hadoop ecosystems to manage storage and support scalable data operations.<br>• Integrate streaming and event-driven data using Apache Kafka to improve data availability and timeliness.<br>• Monitor data workflows, troubleshoot processing issues, and implement improvements that increase reliability and efficiency.<br>• Collaborate with technical and business stakeholders to understand data needs and translate them into practical engineering solutions.<br>• Document pipeline architecture, data flow logic, and operational procedures to support maintainability and team knowledge sharing.
We are looking for a Data Engineer to help build and maintain scalable data solutions that support critical business operations within the brokerage industry. This role is based in Chicago, Illinois, and focuses on designing reliable data pipelines, improving data accessibility, and enabling efficient processing across large datasets. The ideal candidate brings strong technical expertise in modern data engineering tools and enjoys working in a fast-paced environment where data quality, performance, and consistency are essential.<br><br>Responsibilities:<br>• Design, develop, and optimize data pipelines that support ingestion, transformation, and delivery of large-scale datasets.<br>• Build and maintain ETL workflows to ensure accurate, timely, and dependable movement of data across platforms.<br>• Use Python and Apache Spark to process complex data efficiently and improve overall pipeline performance.<br>• Work with Apache Hadoop technologies to manage distributed data storage and computation for high-volume workloads.<br>• Implement streaming and messaging solutions with Apache Kafka to support near-real-time data integration needs.<br>• Partner with cross-functional teams to understand data requirements and translate business needs into technical solutions.<br>• Monitor data processes, troubleshoot issues, and resolve bottlenecks to maintain system reliability and data integrity.<br>• Contribute to enhancements involving data platform changes or internal process updates as part of ongoing engineering initiatives.
<p>We are looking for a Data Engineer to build and enhance reporting and data solutions that help teams make informed business decisions across the organization. This role partners with groups such as asset management, acquisitions, accounting, and HR to translate business needs into scalable dashboards, reliable data pipelines, and actionable insights. Based in Los Angeles, California, the position is ideal for someone who combines strong technical depth with the ability to explain findings clearly to a range of stakeholders.</p><p><br></p><p>Responsibilities:</p><p>• Create and refine dashboards, reports, and automated data outputs using tools such as Python, Excel, and Power BI to support operational and strategic reporting needs.</p><p>• Examine large and varied datasets to uncover meaningful trends, performance indicators, and opportunities for improvement.</p><p>• Guide and support entry-level BI team members by reviewing work, sharing best practices, and contributing to their career growth.</p><p>• Partner with stakeholders across multiple business functions to define reporting goals, gather technical requirements, and deliver effective data solutions.</p><p>• Translate technical concepts and analytical results into clear recommendations for non-technical audiences.</p><p>• Contribute to cross-department initiatives that improve data availability, reporting consistency, and overall usability of business information.</p><p>• Develop and maintain queries, procedures, and data workflows to support extraction, transformation, and loading activities across reporting environments.</p><p>• Monitor data quality through validation checks, issue resolution, and routine audits to maintain accuracy and reliability.</p><p>• Administer BI platforms with attention to performance, access control, and system stability while assisting users with adoption and training.</p><p><br></p><p>For immediate consideration, apply now and direct message Reid Gormly on LinkedIn</p>
We are looking for a Data Engineer to take ownership of a growing enterprise data platform. This role is best suited for a highly capable, hands-on individual who can build, optimize, and support modern data solutions while working closely with business and technical stakeholders. The position offers the opportunity to shape data architecture, improve data accessibility, and contribute to a scalable analytics environment. This is an onsite role, with three days per week in the office.<br><br>Responsibilities:<br>• Design, build, and maintain scalable data pipelines that support enterprise reporting, analytics, and operational needs.<br>• Develop and enhance data integration workflows using Microsoft Fabric or Azure Data Factory to move and transform data efficiently.<br>• Create and refine data models and architecture standards to improve consistency, performance, and long-term usability across platforms.<br>• Write production-quality Python code to automate data processing, validation, and orchestration tasks.<br>• Partner with cross-functional teams to understand business requirements and translate them into practical data engineering solutions.<br>• Monitor data platform performance, troubleshoot issues, and implement improvements that strengthen reliability and maintainability.<br>• Work with large-scale data technologies such as Spark, Hadoop, Kafka, and ETL frameworks to support evolving data initiatives.<br>• Contribute to the expansion of the data function by documenting processes and, over time, providing guidance to team members as needed.
<p>We are looking for an experienced Data Engineer to join a manufacturing organization. In this role, you will create and maintain modern data platforms within Microsoft Fabric, enabling dependable reporting, analytics, and business decision-making.</p><p><br></p><p>Responsibilities:</p><p>• Build and support end-to-end data solutions in Microsoft Fabric, including pipelines, lakehouses, warehouses, and semantic models.</p><p>• Develop scalable data workflows that collect, transform, and organize information from multiple business sources for analytical use.</p><p>• Partner with analysts, developers, IT teams, and business users to understand data needs and deliver practical reporting and analytics capabilities.</p><p>• Maintain data quality, governance, and security standards to ensure information is accurate, consistent, and appropriately controlled.</p><p>• Monitor and optimize data processing performance to improve reliability, efficiency, and overall platform stability.</p><p>• Troubleshoot data issues, resolve pipeline failures, and provide ongoing support for production data environments.</p><p>• Document technical designs, data flows, and operational procedures to support maintainability and team collaboration.</p>
<p>We are looking for a Data Engineer to help build and maintain reliable data solutions for a client. This position focuses on moving, transforming, and validating data from multiple sources to support reporting, analytics, and operational needs. The ideal candidate will be comfortable working with modern cloud data platforms, collaborating with cross-functional teams, and improving data processes for accuracy, consistency, and timely delivery.</p><p><br></p><p>Responsibilities:</p><p>• Design, develop, and maintain data pipelines that ingest information from APIs, files, network sources, and other internal or external systems.</p><p>• Build and enhance automated data workflows using Snowflake, Azure Data Factory, Python, and SQL to support reporting and analytics needs.</p><p>• Apply business rules to transform raw data into structured, usable datasets for analysts, stakeholders, and downstream applications.</p><p>• Partner with business users, analysts, developers, and project teams to gather requirements and deliver data solutions within an agile environment.</p><p>• Monitor data quality by validating, cleansing, and reconciling datasets to ensure dependable and consistent information availability.</p><p>• Troubleshoot pipeline failures, data inconsistencies, and integration issues, then implement fixes to improve system stability.</p><p>• Maintain clear documentation for data warehouse configurations, workflow logic, and processing standards.</p><p>• Manage code and workflow changes through version control practices to support traceability and controlled deployment.</p><p>• Improve the timeliness and efficiency of data delivery for internal teams and third-party data consumers by identifying process enhancements.</p>
We are looking for a Data Engineer to help design and enhance data solutions that support reliable reporting and analytics in Salt Lake City, Utah. This role focuses on building scalable data pipelines, shaping well-structured warehouse models, and improving the quality and usability of enterprise data assets. The ideal candidate brings strong experience with SQL, Python, AWS technologies, and dimensional modeling principles grounded in the Kimball methodology.<br><br>Responsibilities:<br>• Build and maintain data pipelines that ingest, transform, and prepare information for downstream analytics and business use.<br>• Design warehouse structures using Kimball-based dimensional modeling practices to support clear, consistent reporting.<br>• Develop and optimize SQL- and Python-driven data workflows with an emphasis on scalability, performance, and maintainability.<br>• Partner with analysts, engineers, and business stakeholders to translate data needs into practical engineering solutions.<br>• Create and manage data transformation logic using dbt to improve testing, documentation, and deployment consistency.<br>• Support cloud-based data platforms in an AWS environment and contribute to ongoing improvements in data architecture.<br>• Monitor data quality and troubleshoot pipeline issues to ensure dependable delivery of curated datasets.<br>• Contribute to modern data engineering practices, including tools such as PySpark when needed for larger-scale processing.
<p>We are looking for a Data Engineer to join an opportunity in Atlanta, Georgia. In this role, you will design and support reliable data solutions that enable efficient reporting, analytics, and downstream business insights across cloud-based platforms. The ideal candidate brings strong engineering fundamentals, enjoys working with diverse data sets, and can help shape scalable architecture in a collaborative enterprise environment.</p><p><br></p><p>Responsibilities:</p><p>• Design, build, and maintain robust data pipelines that move and transform information from a variety of internal and external sources.</p><p>• Develop efficient integration processes to unify structured and unstructured data for analytics, reporting, and operational use cases.</p><p>• Improve the speed, reliability, and scalability of existing data workflows through tuning, monitoring, and process optimization.</p><p>• Create and refine data models that support business intelligence, advanced analytics, and decision-making needs.</p><p>• Administer and enhance cloud-based data environments across modern platforms, ensuring stability, security, and performance.</p><p>• Partner closely with analytics and business teams to understand data needs and deliver accessible, high-quality datasets.</p><p>• Implement ETL solutions using Python, Spark, and cloud-native services to support enterprise data operations.</p><p>• Contribute to best practices for data engineering, documentation, and cross-functional collaboration within a consultative delivery model</p>
We are looking for a Data Engineer to build and enhance scalable data solutions that support analytics and business decision-making in Jacksonville, Florida. This role focuses on designing reliable warehouse structures, developing efficient data pipelines, and improving data quality across enterprise platforms. The ideal candidate brings strong technical depth in modern data engineering practices and is comfortable partnering with cross-functional teams to deliver well-governed, high-performing data assets.<br><br>Responsibilities:<br>• Design and maintain enterprise data warehouse solutions using dimensional modeling techniques that support reporting, analytics, and long-term scalability.<br>• Develop, orchestrate, and optimize ETL and ELT workflows for batch and near real-time data movement using modern pipeline and scheduling tools.<br>• Build robust data architectures across cloud-based platforms while balancing performance, resilience, and cost efficiency.<br>• Troubleshoot pipeline failures, data inconsistencies, and performance bottlenecks, then implement practical fixes that improve reliability and throughput.<br>• Apply governance standards by supporting data quality controls, metadata practices, lineage visibility, and role-based access management.<br>• Partner with business and technical stakeholders to translate data needs into well-structured solutions and provide clear updates on progress, risks, and delivery timelines.<br>• Create efficient code for data transformation and aggregation using Python and advanced query development techniques.<br>• Integrate data from databases, APIs, streaming platforms, and external sources to support a broad range of analytical use cases.<br>• Mentor team members and contribute ideas that streamline processes, reduce friction, and strengthen engineering best practices.
We are looking for a Data Engineer to support scalable data solutions for a Long-term Contract position based in Cincinnati, Ohio. This role focuses on building reliable data pipelines, optimizing data movement across platforms, and enabling efficient access to high-quality datasets for business and technical teams. The ideal candidate brings strong hands-on experience with modern big data tools and a practical approach to designing robust ETL workflows.<br><br>Responsibilities:<br>• Design and maintain end-to-end data pipelines that process large and complex datasets with a focus on performance and reliability.<br>• Develop ETL workflows using Python and Spark to transform raw data into structured, usable formats for downstream consumption.<br>• Work with Hadoop-based environments to manage distributed data processing and storage activities at scale.<br>• Integrate streaming and messaging components such as Kafka to support near real-time data ingestion and event-driven processing.<br>• Monitor pipeline health, troubleshoot data issues, and implement improvements that strengthen stability and data quality.<br>• Collaborate with analysts, developers, and other stakeholders to understand data needs and translate them into technical solutions.<br>• Improve existing data architecture by refining workflows, reducing processing bottlenecks, and increasing operational efficiency.
We are looking for a Data Engineer to join our team in Texas. In this role, you will create and enhance modern cloud data platforms that power reporting, analytics, and intelligent business solutions. The position is ideal for a hands-on individual who excels at building scalable pipelines, improving data performance, and partnering with technical and business teams to deliver reliable data products.<br><br>Responsibilities:<br>• Create and maintain cloud-based data solutions on Azure using services such as Databricks, Synapse Analytics, Data Factory, and related platform tools.<br>• Build resilient data pipelines and integration workflows that support enterprise analytics, reporting, and business intelligence across large and complex datasets.<br>• Architect and implement lakehouse and warehouse environments, including layered data models that organize raw, refined, and business-ready data.<br>• Develop reusable notebooks and processing frameworks with Python, PySpark, Spark, and Scala to support scalable engineering patterns.<br>• Tune and troubleshoot data workloads to improve speed, stability, scalability, and overall cost efficiency in production environments.<br>• Deliver end-to-end data solutions by handling design, development, testing, deployment, documentation, and ongoing operational support.<br>• Apply source control, DevOps practices, and automated release processes to enable consistent and secure deployments.<br>• Partner with stakeholders, engineers, and leadership to convert business needs into practical technical designs and data solutions.<br>• Support AI and machine learning initiatives through data preparation, feature development, curated datasets, and platform capabilities for advanced analytics.<br>• Investigate production issues, evaluate new technologies, and recommend improvements that strengthen reliability, efficiency, and business value.
We are looking for a Data Engineer to join a hybrid team in Massachusetts in a contract capacity with the potential to become permanent. This role focuses on designing dependable data solutions that support reporting, analytics, and broader business needs. The ideal candidate brings hands-on experience with modern cloud data platforms and enjoys improving data flow, structure, and performance across production environments.<br><br>Responsibilities:<br>• Design, build, and enhance scalable data pipelines that support reliable movement and transformation of enterprise data.<br>• Create and refine Snowflake data models to ensure efficient storage, accessibility, and performance for downstream use.<br>• Bring new internal and external data sources into existing workflows while maintaining consistency and integrity across systems.<br>• Track pipeline health, investigate processing issues, and resolve data anomalies to keep production operations stable.<br>• Strengthen data workflows through automation, process optimization, and improved operational efficiency.<br>• Work closely with analysts, architects, software engineers, and business partners to deliver dependable data solutions aligned with organizational goals.<br>• Produce clear technical documentation covering pipeline logic, data processes, and engineering standards.<br>• Apply data quality checks, validation methods, and error-handling practices to support trustworthy and governed datasets.
We are looking for a Senior Data Engineer to develop and optimize enterprise data systems that support analytics and digital solutions. In this role, you will design and implement robust data architectures, ensuring seamless data integration and transformation processes across the organization. Your expertise will drive the creation of reliable pipelines and scalable infrastructure, enabling advanced analytics and machine learning capabilities.<br><br>Responsibilities:<br>• Design and implement scalable data pipelines using Databricks, Spark, and Delta Lake to support enterprise-level analytics.<br>• Develop and maintain efficient data models tailored for AI, analytics, and operational systems.<br>• Lead Master Data Management initiatives to establish unified and accurate data records across platforms.<br>• Create batch and near-real-time data processing workflows for structured and semi-structured datasets.<br>• Collaborate with AI and software development teams to ensure delivery of high-quality datasets for machine learning.<br>• Define and enforce data architecture standards, ensuring scalability, reliability, and governance.<br>• Troubleshoot and optimize data systems to maintain performance and reliability in complex environments.<br>• Partner with cloud and IT teams to integrate modern data platforms and ensure seamless functionality.
We are looking for a Data Engineer to join a fast-paced IT consulting environment in Atlanta, Georgia. In this role, you will design and optimize modern data solutions that support analytics, machine learning, and business decision-making across a variety of client initiatives. The ideal candidate brings strong technical depth in cloud-based data engineering along with a practical, solution-oriented mindset. This position is well suited for someone who enjoys turning complex data challenges into scalable and reliable platforms.<br><br>Responsibilities:<br>• Build and maintain robust data pipelines that move, transform, and prepare information for reporting, analytics, and operational use.<br>• Design end-to-end data solutions within Azure-based environments, using the right services and frameworks to support performance, reliability, and scale.<br>• Develop engineering workflows with Python and PySpark to process both structured datasets and more complex unstructured sources.<br>• Create and support data architecture components in Microsoft Fabric, Databricks, and related platforms to enable efficient data access and delivery.<br>• Implement pipeline orchestration and workflow automation through Databricks tools to streamline recurring data operations.<br>• Support machine learning initiatives by preparing high-quality datasets and building pipelines that feed model development and deployment processes.<br>• Apply sound data management practices to ensure consistency, usability, and governance across data assets.<br>• Work within Azure DevOps-driven delivery environments to contribute to version control, deployment processes, and collaborative engineering practices.<br>• Partner with stakeholders to understand business objectives, translate requirements into technical solutions, and deliver strong client-focused outcomes.
We are looking for an experienced Data Engineer to join a construction and contractor-focused organization in Appleton, Wisconsin. This contract opportunity with potential for a permanent role is ideal for a senior-level candidate who enjoys building scalable cloud-based data platforms, working hands-on with Python and notebook-driven development, and applying AI-enabled tools to create practical business solutions. The role will focus on designing modern data lake capabilities, improving data movement and transformation processes, and partnering with stakeholders to deliver reliable analytics infrastructure.<br><br>Responsibilities:<br>• Design, build, and enhance modern data lake architecture in Google Cloud Platform to support scalable and efficient data operations.<br>• Develop robust data pipelines using Python, SQL, Spark, and ETL frameworks to ingest, transform, and prepare data from multiple sources.<br>• Create and maintain notebook-based solutions that demonstrate clear technical approaches, reusable logic, and well-documented project outcomes.<br>• Integrate large-scale data processing technologies such as Hadoop and Kafka to support high-volume and streaming data workloads.<br>• Collaborate with cross-functional teams to translate business needs into data engineering solutions that improve reporting, analytics, and operational decision-making.<br>• Apply AI-driven tools and approaches to accelerate development, improve solution quality, and deliver innovative customer-focused outcomes.<br>• Support cloud data environments that may include Azure Data Lake and related platforms as part of broader enterprise data initiatives.<br>• Contribute to data platform improvements, including work connected to enterprise tool adoption or internal platform changes when needed.
We are looking for a Data Engineer to join a growing financial services organization in Chicago, Illinois. This contract opportunity with potential for a permanent role is ideal for someone who enjoys building in a developing data environment, contributing to a modern cloud-based platform, and helping shape the next phase of the team’s capabilities. You will work closely with key data stakeholders in a nimble setting where initiative, sound judgment, and adaptability are highly valued.<br><br>Responsibilities:<br>• Design and support data workflows that collect, refine, and deliver information across a contemporary cloud ecosystem.<br>• Develop and enhance scalable data pipelines using Python and automated ingestion platforms such as Fivetran or comparable tools.<br>• Model and transform datasets within Snowflake to enable reliable analytics and downstream business intelligence reporting.<br>• Collaborate closely with the data architect to expand and improve the organization’s overall data infrastructure.<br>• Contribute to reporting readiness by preparing curated datasets for visualization tools including Power BI and Sigma.<br>• Monitor pipeline performance and resolve data issues to maintain accuracy, consistency, and dependable delivery.<br>• Assess emerging technologies and recommend practical additions to the data stack as business needs evolve.<br>• Work effectively in a fast-paced team environment where priorities can shift and new tooling may be introduced regularly.
We are looking for a senior-level Data Engineer to shape and deliver a scalable data platform in Kalamazoo, Michigan. This role combines strategic architecture with hands-on engineering, creating reliable data products that support reporting, advanced analytics, and AI-driven solutions. The ideal candidate will build secure, multi-tenant data capabilities with strong attention to privacy, governance, and long-term platform quality.<br><br>Responsibilities:<br>• Lead the design of a modern data platform that supports ingestion, transformation, storage, and consumption across analytical and operational use cases.<br>• Build and maintain robust batch and streaming pipelines that move data from relational systems, object storage, document databases, and event sources into centralized platforms.<br>• Define data architecture standards, modeling approaches, and engineering practices that improve consistency, reliability, and scalability across the organization.<br>• Create multi-tenant data solutions with strong isolation controls, secure access patterns, and governance measures built into the platform design.<br>• Develop data models and serving layers that enable enterprise reporting, self-service analytics, and AI or machine learning workloads.<br>• Evaluate cloud-based data services, processing frameworks, and warehouse technologies to ensure the platform meets performance, cost, and security expectations.<br>• Partner with product, engineering, and leadership teams to explain technical decisions, highlight risks, and align platform investments with business priorities.<br>• Oversee external vendors and implementation partners by reviewing recommendations, challenging misaligned approaches, and enforcing internal data standards.