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.
We are looking for a Data Engineer to support enterprise data movement and application integration efforts in Boston, Massachusetts. This Long-term Contract position will focus on building, maintaining, and enhancing custom services that transfer, load, and transform data across multiple systems. The role works closely with technical and business teams to deliver reliable integration solutions using .NET/C#, APIs, and modern deployment practices.<br><br>Responsibilities:<br>• Design, support, and improve custom integration services that move data between enterprise platforms and applications.<br>• Build and maintain ETL processes for data loading, transformation, and system-to-system exchange.<br>• Develop microservice-based solutions in .NET/C# to replace larger legacy integration components where needed.<br>• Create and support API-driven integrations, including services that rely on REST and SOAP protocols.<br>• Partner with business analysts, developers, and solution stakeholders to translate operational needs into technical data workflows.<br>• Monitor data pipelines and integration jobs, troubleshoot failures, and resolve performance or reliability issues.<br>• Contribute to deployment and release activities using Azure DevOps or comparable CI/CD tools.<br>• Support integrations involving key enterprise platforms such as Salesforce and higher education systems when applicable.
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><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>We are looking for a Contract Data Engineer to support financial systems and data operations in San Francisco, California. This is a remote on-going contract. This role will work across Finance, Systems, and Engineering to improve data reliability, strengthen integrations, and enhance platforms that support billing, accounts payable, and quote-to-cash workflows. The ideal candidate brings deep technical expertise with NetSuite and Snowflake, along with strong coding skills to diagnose issues, streamline processes, and build scalable solutions in a complex systems environment.</p><p><br></p><p>Responsibilities:</p><p>• Build, monitor, and refine data pipelines that move financial and transactional information across internal platforms and enterprise systems.</p><p>• Investigate data issues, resolve integration failures, and improve the overall accuracy and consistency of business-critical datasets.</p><p>• Develop and maintain middleware solutions that connect NetSuite, Salesforce, Snowflake, and custom applications.</p><p>• Partner with Finance, Systems, and Engineering stakeholders to deliver technical enhancements that support accounting operations and downstream reporting.</p><p>• Implement improvements within NetSuite and related financial systems to better support billing, accounts payable, and quote-to-cash processes.</p><p>• Troubleshoot code and system behaviors using SQL, Python, and related tools to identify root causes and restore reliable performance.</p><p>• Support integration workflows between Salesforce and NetSuite, ensuring stable data exchange and operational continuity.</p><p>• Evaluate and contribute to automation initiatives, including AI-enabled workflow opportunities that can reduce manual effort and improve efficiency.</p>
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 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.
<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>
We are looking for a Data Engineer to join our team in Jacksonville, Florida and help shape scalable, enterprise-ready analytics solutions. In this role, you will turn complex business needs into well-structured data models, high-performing pipelines, and actionable reporting assets that support informed decision-making. The ideal candidate brings deep experience with modern data platforms, strong technical leadership, and the ability to guide best practices for analytics, governance, and data usability across the organization.<br><br>Responsibilities:<br>• Design and maintain scalable data pipelines and transformation workflows using tools such as Python, Apache Spark, Hadoop, Kafka, and ETL frameworks.<br>• Build and optimize enterprise semantic models that support consistent metrics, reusable analytics assets, and reliable reporting across multiple business areas.<br>• Partner with business and technical stakeholders to convert complex requirements into practical data solutions, dashboards, and analytical datasets.<br>• Develop and support analytics solutions within modern cloud and hybrid environments, with a strong focus on Microsoft Power BI, Microsoft Fabric, and Azure Synapse Analytics.<br>• Improve data quality, model performance, and platform reliability through testing, validation, tuning, and adherence to established governance standards.<br>• Provide technical guidance to team members by sharing best practices in data modeling, visualization, and scalable analytics design.<br>• Evaluate and incorporate AI-enabled analytics capabilities and automation opportunities while ensuring outputs align with business needs and quality expectations.<br>• Communicate technical concepts and analytical insights clearly to a range of audiences, including leadership, to support strategic decisions.
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 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.
<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>
<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>
We are looking for a Data Engineer to join a growing team in Conshohocken, Pennsylvania within the financial services industry. In this role, you will build and enhance modern data pipelines and warehouse structures that support reporting, analytics, and business decision-making. You will partner with technical and business teams to deliver reliable, well-governed data solutions using Python, Azure Synapse Analytics, and related cloud technologies.<br><br>Responsibilities:<br>• Build and support scalable data pipelines using Python, including PySpark, within Azure Synapse Analytics notebooks and pipeline workflows.<br>• Design, load, and maintain warehouse structures in a massively parallel processing environment, applying dimensional modeling concepts such as facts and dimensions.<br>• Ingest and transform data from a range of sources, including APIs, databases, and flat files, to create dependable datasets for downstream use.<br>• Improve the efficiency and reliability of Azure Synapse processes by tuning queries, refining workloads, and addressing performance constraints.<br>• Partner with data architects, analysts, and other stakeholders to translate business needs into practical data models and engineering solutions.<br>• Establish validation routines and data quality controls to promote completeness, consistency, and accuracy across datasets.<br>• Monitor scheduled jobs and pipeline activity, troubleshoot failures, and implement corrective actions to maintain service levels.<br>• Document data flows, transformation logic, technical configurations, and operating procedures to support maintainability and knowledge sharing.<br>• Apply security, privacy, and governance standards to data solutions while supporting broader data platform initiatives such as lakes, lakehouses, and cataloging practices.
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 mission-driven team, where you will design and support the data foundation behind clinical reporting, advanced analytics, and predictive healthcare solutions. This contract position offers the opportunity to build dependable, scalable data workflows that deliver information from healthcare platforms and other source systems to clinicians and business teams. The role is highly hands-on and centers on transforming complex healthcare data into trusted, well-structured assets that support operational and clinical decision-making.<br><br>Responsibilities:<br>• Design, develop, and maintain robust data pipelines that move information from healthcare platforms and related source systems into analytics and reporting environments.<br>• Prepare, standardize, and validate data from claims, clinical records, and social determinants of health sources to ensure accuracy and usability.<br>• Apply sound data modeling practices to organize information for warehousing, business intelligence, and advanced analytical use cases.<br>• Build scalable processing solutions using tools such as Python, Apache Spark, Hadoop, and Kafka to support high-volume data operations.<br>• Partner with analytics, clinical, and business stakeholders to deliver reliable datasets that power descriptive, predictive, and prescriptive insights.<br>• Monitor pipeline performance, troubleshoot data issues, and improve the reliability and efficiency of end-to-end ETL processes.<br>• Support the full lifecycle of data initiatives, from source integration and transformation through delivery for reporting and analytical applications.
<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>
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 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.
<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>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 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.
Position: Data Engineer<br>Location: Oskaloosa, IA / Des Moines, IA -- Onsite<br>Salary: $100,000 - $120,000 base + exceptional benefits<br><br>*** For immediate and confidential consideration, please APPLY and EMAIL YOUR RESUME to MEREDITH CARLE . My email can be found on my LinkedIn page. ***<br><br>Data Engineer<br>Shape the Future of Enterprise Analytics, AI & Data Innovation<br>Are you the type of data professional who sees a business problem and immediately starts thinking about how to model, engineer, and deliver the right solution?<br>A highly successful, technology-driven organization is seeking a Data Engineer to help build the foundation for enterprise analytics, business intelligence, governance, and next-generation AI initiatives. This is an opportunity to make a visible impact across the business while working alongside a collaborative team of data professionals who are passionate about solving complex challenges.<br>This role is ideal for someone who enjoys being hands-on, partnering with the business, and building modern data solutions that drive meaningful outcomes.<br>What You'll Do<br> • Design and develop scalable data models, semantic layers, and enterprise data solutions<br> • Build trusted data structures that support analytics, reporting, AI, and business intelligence initiatives<br> • Develop and optimize cloud-based data pipelines and integrations<br> • Improve data governance, lineage, metadata management, and observability practices<br> • Create automated data quality and validation frameworks<br> • Implement CI/CD processes and modern DataOps best practices<br> • Optimize SQL performance across warehouses, lakehouses, and reporting environments<br> • Partner with analysts and business stakeholders to transform complex problems into actionable solutions<br> • Contribute to technical standards, mentoring, documentation, and architectural best practices<br>What We're Looking For<br>Core Qualifications<br> • Strong experience with data modeling and semantic modeling<br> • Hands-on experience with Microsoft Fabric, Azure, and Power BI<br> • Advanced SQL development and performance optimization skills<br> • Experience with Git, CI/CD, and modern data engineering practices<br> • Ability to translate business requirements into scalable technical solutions<br> • Experience developing enterprise data pipelines and analytics platforms<br> • A plus if you have data governance, data warehouse, data lake and or DBT experience.<br><br>*** For immediate and confidential consideration, please APPLY and EMAIL YOUR RESUME to MEREDITH CARLE . My email can be found on my LinkedIn page. Also, you may contact me at 515-303-4654. Or one click apply on our Robert Half website. No third party inquiries please. Our client cannot provide sponsorship and cannot hire C2C. ***
<p>A Manufacturing/ distribution company is looking for a Data Engineer with 3 + years of experience to join a dynamic team in Oklahoma City, Oklahoma. In this role, you will play a crucial part in designing and maintaining data infrastructure to support analytics and decision-making processes. You will be a key contributor in developing, optimizing, and maintaining the data infrastructure that supports analytics and business intelligence initiatives, and data driven decision-making using Snowflake, Matillion, and other tools. Position will be in-office to work closely with the team. You must live in the Oklahoma City area. Client is unable to sponsor. No 3rd parties please.</p><p><br></p><p>Responsibilities:</p><p><br></p><p>• Design, develop, and maintain scalable data pipelines to support data integration and real-time processing.</p><p>• Implement and manage data warehouse solutions, with a strong focus on Snowflake architecture and optimization.</p><p>• Write efficient and effective scripts and tools using Python to automate workflows and enhance data processing capabilities.</p><p>• Work with SQL Server to design, query, and optimize relational databases in support of analytics and reporting needs.</p><p>• Monitor and troubleshoot data pipelines, resolving any performance or reliability issues.</p><p>• Ensure data quality, governance, and integrity by implementing and enforcing best prac</p>
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.