<p><strong>Robert Half is working with a client who is looking to hire a Data Architect</strong> to help define the architecture and technical direction of a major enterprise data modernization initiative.</p><p>This individual will be responsible for designing scalable data platforms, establishing enterprise data standards, and providing architectural guidance across engineering, analytics, reporting, and AI initiatives.</p><p>Responsibilities</p><ul><li>Design enterprise data architecture across cloud and on-premise environments.</li><li>Define architectural standards for data ingestion, storage, transformation, governance, and consumption.</li><li>Develop conceptual, logical, and physical data models.</li><li>Provide technical direction to Data Engineers and Analytics teams.</li><li>Evaluate technologies and recommend appropriate data platform solutions.</li><li>Design integrations across ERP, CRM, operational, and third-party systems.</li><li>Partner with security and governance teams to establish data controls.</li><li>Support cloud migration and data platform modernization projects.</li><li>Create architecture diagrams, roadmaps, and technical documentation.</li></ul><p><br></p>
We are looking for an experienced Data/Information Architect to shape and advance a modern cloud-based data environment. This long-term contract opportunity is well suited for someone who can define scalable architecture, optimize data flow, and support enterprise reporting and analytics needs. The role centers on designing high-performing Snowflake solutions, establishing strong data models, and connecting information from multiple business platforms into a unified ecosystem.<br><br>Responsibilities:<br>• Define and evolve the overall architecture for a cloud data platform with a focus on scalability, reliability, and long-term performance.<br>• Create Snowflake-based solutions that support efficient data storage, transformation, and consumption for analytics and reporting.<br>• Develop logical and physical data models that improve consistency, usability, and governance across enterprise datasets.<br>• Integrate data from a range of internal business applications and external sources to build a connected and dependable information framework.<br>• Partner with technical and business stakeholders to translate reporting and analytical goals into practical architectural designs.<br>• Establish standards for data organization, documentation, and file management to support accuracy, accessibility, and compliance needs.<br>• Review existing data processes and recommend improvements that strengthen platform efficiency, quality, and maintainability.<br>• Provide architectural guidance on digital content and documentation-related data structures where they intersect with enterprise information systems.
<p>We are seeking a Data Engineer to develop and maintain scalable data pipelines and cloud-based data platforms. This role will work closely with analytics and business teams to deliver reliable, high-quality data solutions.</p><p>Responsibilities</p><ul><li>Build and maintain ETL/ELT processes.</li><li>Develop data pipelines for structured and unstructured data.</li><li>Support enterprise data warehouse solutions.</li><li>Optimize data models and database performance.</li><li>Implement data quality and governance standards.</li><li>Collaborate with business intelligence teams.</li></ul><p><br></p>
<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>Lead Data Engineer</p><p>Salary: Up to $160,000 Location:</p><p>On-Site | South Los Angeles Area</p><p>Employment Type: Full-Time</p><p><br></p><p>Build the Foundation for Enterprise Analytics</p><p><br></p><p>We are seeking a Lead Data Engineer to drive the architecture, modernization, and expansion of a growing enterprise data platform built within the Microsoft Azure ecosystem. This is a highly visible technical leadership role where you'll help shape the future of data across multiple business functions by building scalable, secure, and high-performing data solutions.</p><p><br></p><p>If you're passionate about Databricks, cloud data platforms, and mentoring engineering teams while remaining hands-on with development, this is an opportunity to make a significant impact.</p><p><br></p><p>What You'll Do</p><ul><li>Lead the design, implementation, and optimization of an enterprise Azure Databricks Lakehouse environment utilizing Bronze, Silver, and Gold data layers.</li><li>Architect and execute migrations from SQL Server and legacy platforms into modern cloud-native data solutions.</li><li>Develop and optimize large-scale ETL/ELT pipelines supporting operational reporting, business intelligence, advanced analytics, and data science initiatives.</li><li>Integrate data from multiple enterprise systems, APIs, operational platforms, and third-party sources.</li><li>Establish best practices for data engineering, data modeling, testing, CI/CD, monitoring, governance, and production support.</li><li>Implement and maintain data governance frameworks, security controls, lineage tracking, and access management.</li><li>Lead code reviews, technical design discussions, and engineering standards across the data team.</li><li>Mentor and support data engineers while fostering a culture of technical excellence.</li><li>Partner closely with business stakeholders, analysts, and data scientists to deliver trusted, scalable data products.</li></ul><p>For immediate consideration, apply now and direct message Reid Gormly on LINKEDIN</p>
<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>
<p>We are looking for a Data Engineer to join a Chemicals Manufacturing organization in New Jersey in a contract-to-permanent capacity. This role focuses on creating reliable, secure, and scalable data solutions that connect operational and business systems to enterprise reporting, analytics, and advanced data use cases. The position will work across IT and operational environments to support trusted data delivery for functions such as finance, supply chain, operations, commercial teams, and corporate analytics.</p><p><br></p><p>Responsibilities:</p><p>• Design, build, and maintain large-scale data pipelines that move information from enterprise and operational source systems into structured data layers for analytics and reporting.</p><p>• Develop curated and semantic data models that support business intelligence platforms, downstream applications, and data-driven decision-making across the organization.</p><p>• Connect manufacturing and operational technology data sources using approved integration methods while coordinating with plant and controls teams to protect system reliability and safety.</p><p>• Establish data quality standards through validation rules, automated testing, and monitoring processes that improve accuracy, completeness, and timeliness of delivered datasets.</p><p>• Implement observability practices such as lineage tracking, alerting, and operational runbooks to strengthen support processes and reduce production issues.</p><p>• Apply security and governance controls including access management, secrets handling, data classification, and retention practices aligned with enterprise policies.</p><p>• Automate deployment workflows with Git-based CI/CD processes to promote consistent releases across environments and improve delivery reliability.</p><p>• Tune platform performance and resource usage by optimizing processing strategies, scaling approaches, and storage patterns to balance speed and cost.</p><p>• Partner with BI, data, and IT stakeholders to define data contracts, document solutions, and provide operational knowledge transfer to internal teams and external partners.</p><p><br></p><p><br></p><p>02710-0013476075</p><p><br></p>
We are looking for a Data Engineer to join a Long-term Contract opportunity based in Cincinnati, Ohio. This role will help shape enterprise-grade data applications by combining strong engineering practices with thoughtful user-focused delivery, supporting solutions that turn complex information into reliable business insights. The position works closely with cross-functional teams to build scalable data pipelines, enable high-quality analytics, and contribute to modern application experiences that are secure, dependable, and easy to use.<br><br>Responsibilities:<br>• Design and build scalable data pipelines that collect, transform, and deliver enterprise data for analytics and application use.<br>• Develop and maintain ETL workflows using Python, Apache Spark, Hadoop, and Kafka to support reliable movement of large and complex datasets.<br>• Partner with business, analytics, backend, and cloud teams to translate reporting and decision-support needs into practical data engineering solutions.<br>• Establish reusable standards for data integration, quality checks, and processing patterns to improve consistency across products.<br>• Optimize data workflows for performance, stability, and maintainability in production environments.<br>• Support secure integration between data platforms, governed datasets, and downstream applications or APIs.<br>• Contribute to testing, monitoring, and troubleshooting practices to ensure dependable data availability and issue resolution.<br>• Document data processes, technical decisions, and implementation standards so teams can scale solutions more effectively.
We are looking for a Data Engineer to help build reliable data solutions that support reporting, analytics, and day-to-day business decisions in Princeton, New Jersey. This position focuses on creating scalable data flows, improving platform performance, and organizing data for efficient access across teams. The ideal candidate brings strong technical depth in pipeline development, database technologies, and cloud-based data environments.<br><br>Responsibilities:<br>• Build, enhance, and support scalable ETL workflows that move and transform data from multiple sources into trusted analytical platforms.<br>• Create and refine data models, storage structures, and warehouse solutions to improve accessibility, efficiency, and long-term maintainability.<br>• Monitor data processes to identify issues, strengthen reliability, and maintain high standards for accuracy, consistency, and performance.<br>• Partner with analytics, engineering, and business stakeholders to understand data needs and deliver practical data solutions.<br>• Optimize SQL Server and related data systems to support efficient querying, integration, and operational stability.<br>• Implement and maintain orchestration processes using tools such as Airflow or comparable workflow technologies.<br>• Contribute to cloud-based data infrastructure initiatives across platforms such as Azure and other enterprise cloud environments.
<p>We are looking for Data Engineering and Analytics Engineering professionals interested in exploring new opportunities with growing organizations across the Pittsburgh market. We are partnering with multiple companies that are investing in modern data platforms, cloud infrastructure, and enterprise analytics initiatives.</p><p><br></p><p><strong>Location:</strong> Pittsburgh, PA (Hybrid, Remote, and Onsite Opportunities Available)</p><p><strong>Compensation:</strong> $80,000 - $160,000+ depending on experience and position</p><p><strong>Schedule:</strong> Full-Time</p><p><br></p><p><strong>Opportunities May Include:</strong></p><ul><li>Data Engineer</li><li>Senior Data Engineer</li><li>Analytics Engineer</li><li>Data Platform Engineer</li><li>Data Warehouse Engineer</li><li>Cloud Data Engineer</li><li>ETL/ELT Developer</li><li>Data Architect</li><li>Lead Data Engineer</li></ul><p><strong>Responsibilities:</strong></p><ul><li>Design, develop, and maintain scalable data pipelines and data platforms</li><li>Build and optimize ETL/ELT processes supporting analytics and business operations</li><li>Develop and manage cloud-based data solutions and data warehouses</li><li>Partner with analytics, business, and technology teams to deliver trusted data products</li><li>Ensure data quality, reliability, governance, and performance across enterprise environments</li><li>Automate data workflows and support modern data engineering best practices</li><li>Support reporting, analytics, AI, and machine learning initiatives through effective data architecture</li></ul>
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 growing team supporting data-driven initiatives within the energy and natural resources sector in Houston, Texas. This contract position with the potential to become permanent is ideal for someone who enjoys building reliable data pipelines, improving data accessibility, and working with modern big data technologies. The role offers the opportunity to contribute to scalable data solutions that support operational and business insights.<br><br>Responsibilities:<br>• Design, build, and maintain scalable data pipelines to collect, transform, and deliver data from multiple sources<br>• Develop and optimize ETL workflows to support analytics, reporting, and downstream applications<br>• Use Python and Apache Spark to process large-volume datasets efficiently and reliably<br>• Work with Hadoop-based environments to manage distributed data storage and processing needs<br>• Implement and support Kafka-based data streaming solutions for real-time data movement<br>• Partner with technical and business stakeholders to understand data requirements and translate them into practical engineering solutions<br>• Monitor pipeline performance, troubleshoot data issues, and improve overall data quality and reliability
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 help shape and strengthen the organization’s data warehouse and analytics capabilities. This role will focus on building reliable data solutions that support reporting, business intelligence, and operational decision-making across the company. The ideal candidate brings strong technical depth in data engineering, enjoys solving complex integration challenges, and works effectively with both IT colleagues and business stakeholders.</p><p><br></p><p>Responsibilities:</p><p>• Design and enhance scalable data warehouse structures and integration pipelines that support analytics, reporting, and cross-system data flow.</p><p>• Develop, test, and maintain ETL processes that move data from varied source systems into staging, warehouse, and downstream reporting environments.</p><p>• Partner with business teams and technical peers to translate functional needs into practical data solutions and system designs.</p><p>• Improve database performance by tuning SQL, refining indexing strategies, and addressing issues identified through execution plan analysis.</p><p>• Create and support dashboards, reports, and data visualizations using tools such as Power BI, Tableau, and similar business intelligence platforms.</p><p>• Perform data validation, auditing, and quality checks to protect accuracy, consistency, and compliance across critical datasets.</p><p>• Provide production support for data platforms, integrations, and reporting solutions, resolving issues and maintaining dependable system performance.</p><p>• Contribute to agile delivery efforts by participating in development, testing, and quality assurance activities across databases, middleware, and analytics applications</p>
<p>We are looking for a Data Engineer to help strengthen financial decision-making by building reliable data and automation capabilities that support planning and analysis. This position works closely with finance leaders and business partners to turn strategic goals into scalable data solutions, improving visibility, speed, and confidence in reporting. </p><p><br></p><p>Responsibilities:</p><p>• Design and maintain data pipelines that convert financial and operational information into trusted, analysis-ready datasets for planning and reporting.</p><p>• Create scalable data models and structured finance data assets within the broader enterprise ecosystem to support consistent, governed analytics.</p><p>• Develop automation solutions using tools such as Python, Excel, and workflow platforms to streamline recurring finance processes and increase team capacity.</p><p>• Build near real-time data transformation processes that improve the timeliness and accuracy of performance visibility for stakeholders.</p><p>• Apply AI-enabled techniques such as anomaly detection, forecasting support, and variance analysis to enhance financial insight generation.</p><p>• Deliver self-service analytics tools and reporting frameworks that allow business users to explore key metrics and make informed decisions independently.</p><p>• Establish documentation, data standards, and governance practices that improve maintainability, quality, and long-term adoption of solutions.</p><p>• Monitor and support automated jobs and bot-driven processes, including troubleshooting, performance oversight, and control management.</p><p>• Translate complex data findings into clear, executive-level outputs that help guide business strategy and financial priorities</p>
<p>The Data Engineer will develop and maintain scalable data pipelines and cloud-based data solutions that support analytics and business intelligence initiatives.</p><p>Responsibilities</p><ul><li>Design and build ETL/ELT processes.</li><li>Develop data pipelines using Python and SQL.</li><li>Optimize data warehouse performance.</li><li>Work with stakeholders to gather data requirements.</li><li>Support data governance and quality initiatives.</li></ul><p><br></p>
<p>We are seeking an experienced <strong>Data Engineer</strong> to architect, build, and optimize scalable data pipelines and cloud-based data platforms that support advanced analytics, reporting, and business intelligence initiatives.</p><p><strong>Responsibilities</strong></p><ul><li>Design, develop, and maintain robust ETL/ELT pipelines for ingesting, transforming, and loading structured and semi-structured data.</li><li>Build and manage scalable data pipelines using <strong>Python</strong> and <strong>SQL</strong> across cloud and warehouse environments.</li><li>Optimize data storage, query performance, and overall efficiency within modern data warehouse platforms.</li><li>Develop and maintain data models that support downstream analytics, reporting, and operational use cases.</li><li>Collaborate with business stakeholders, analysts, and engineering teams to define data requirements and translate them into technical solutions.</li><li>Implement and support data quality checks, governance standards, and monitoring processes to ensure data reliability and integrity.</li><li>Troubleshoot pipeline failures, performance bottlenecks, and data consistency issues across the data ecosystem.</li><li>Contribute to best practices in data architecture, orchestration, documentation, and deployment.</li></ul><p><br></p>
<p>We are looking for a Data Engineer to design, build, and maintain scalable data pipelines on Microsoft Azure. This role will support enterprise reporting, analytics, and machine learning initiatives by ensuring the availability and integrity of critical business data.</p><p>Responsibilities</p><ul><li>Design and develop ETL/ELT data pipelines</li><li>Build and maintain Azure data platforms and data lakes</li><li>Integrate data from APIs, databases, and third-party systems</li><li>Develop data models supporting analytics and reporting</li><li>Optimize database and pipeline performance</li><li>Implement data quality and monitoring solutions</li><li>Collaborate with analysts, developers, and business users</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 help maintain and improve a mission-driven technology environment that supports essential nonprofit operations in Battle Creek, Michigan. This position blends application support, database engineering, and systems integration work, making it ideal for someone who enjoys solving technical problems across multiple platforms. The role works closely with internal teams and external partners to keep business systems reliable, data accurate, and reporting processes running smoothly.<br><br>Responsibilities:<br>• Maintain and resolve issues across core business applications, including Dynamics 365 Business Central, Microsoft 365, SharePoint, Power BI, procurement tools, workforce systems, and other connected platforms.<br>• Administer Microsoft SQL Server environments by monitoring system health, tuning performance, managing security access, and overseeing backup, recovery, upgrade, and capacity planning activities.<br>• Build, refine, and troubleshoot SQL queries to support operational needs while identifying and correcting data consistency, accuracy, and reconciliation problems between systems.<br>• Develop and support integrations, APIs, ETL processes, Azure Data Factory workflows, scheduled data exchanges, and SFTP-based transfers to ensure dependable movement of information across platforms.<br>• Investigate reporting and data warehouse issues by resolving failed loads, refresh interruptions, and mismatches between source systems and business intelligence outputs.<br>• Contribute to software rollouts and system enhancements through testing, data conversion support, deployment activities, post-launch issue resolution, and production stabilization efforts.<br>• Partner with software vendors and external service providers to diagnose complex technical challenges and drive incidents through to completion.<br>• Create and maintain clear technical documentation for applications, databases, integrations, and data flows while sharing knowledge with teammates to strengthen team coverage.<br>• Support both strategic engineering work and day-to-day technical tasks within a collaborative IT team, adapting to changing priorities as needed.
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 a Data Engineer to help shape and expand a cloud-focused data environment that supports analytics, operational reporting, automation, and emerging AI use cases. Based in Brookfield, Wisconsin, this position works across technical and business teams to deliver dependable data solutions that improve access, accuracy, and usability. The role is ideal for someone who thrives on translating complex data needs into scalable engineering outcomes and values collaboration, problem-solving, and continuous improvement.<br><br>Responsibilities:<br>• Design, build, and maintain scalable data pipelines that move and transform information for analytics, reporting, and operational needs.<br>• Partner with business stakeholders, analysts, software developers, and leaders to understand data requirements and turn them into reliable engineering solutions.<br>• Develop and refine data models and platform architecture to support performance, flexibility, and long-term growth.<br>• Implement ETL processes that integrate data from multiple sources while improving consistency, completeness, and accessibility.<br>• Use Python and distributed data technologies such as Apache Spark and Hadoop to process large and complex datasets efficiently.<br>• Support streaming and event-driven data workflows using tools such as Apache Kafka where real-time data delivery is needed.<br>• Monitor data quality, troubleshoot pipeline issues, and optimize workflows to ensure dependable delivery and strong system performance.<br>• Contribute to ongoing enhancements of the data platform by identifying opportunities to improve scalability, automation, and engineering standards.
<p><strong>Robert Half is working with a client who is looking to hire a Data Engineer</strong> to support a growing enterprise data and analytics initiative. This individual will help build and modernize the data pipelines, integrations, and cloud-based data infrastructure used across the organization.</p><p>The ideal candidate has experience working with large datasets, modern cloud data platforms, and production-grade ETL/ELT pipelines. This role will work closely with Data Architects, Analytics Engineers, BI teams, and business stakeholders as the organization expands its enterprise data capabilities.</p><p>Responsibilities</p><ul><li>Design, build, and maintain scalable ETL/ELT data pipelines.</li><li>Integrate structured and unstructured data from multiple enterprise systems.</li><li>Develop and optimize data models used for analytics and reporting.</li><li>Build solutions within cloud data environments such as Azure, AWS, or GCP.</li><li>Monitor data pipelines for performance, reliability, and data quality.</li><li>Partner with analysts, architects, and application teams to understand data requirements.</li><li>Support the migration of legacy data workloads to modern cloud platforms.</li><li>Develop reusable frameworks and automation for data processing.</li></ul><p><br></p>
We are looking for a Data Engineer to join a team in Santa Monica, California on a Long-term Contract assignment. This position focuses on building dependable data solutions that connect multiple sources, support reporting needs, and improve access to trusted business information. The role offers a blend of pipeline development, dashboard ownership, data quality work, and cross-functional collaboration with partner teams.<br><br>Responsibilities:<br>• Design, validate, and release data pipelines that bring together information from varied source systems within an existing ingestion environment.<br>• Create and support connections to external platforms, APIs, and vendor tools so data remains current, consistent, and available for analysis.<br>• Oversee daily pipeline health, investigate processing issues, and partner with senior engineers to address failures and improve reliability.<br>• Develop and maintain roughly 10 business intelligence dashboards used by 2 to 3 stakeholder groups, keeping reporting useful and aligned with team needs.<br>• Improve dashboard quality by reviewing accuracy, optimizing performance, enhancing usability, and retiring reports that no longer provide value.<br>• Write and maintain data validation checks, including tests at the source level to strengthen data quality and reduce downstream issues.<br>• Support data modeling and transformation efforts using dbt to prepare clean, well-structured datasets for analytics and reporting.<br>• Handle ad hoc data requests submitted through an intake process, providing timely answers to business questions with clear supporting analysis.<br>• Produce and update documentation for pipelines, reporting assets, and operational workflows to promote maintainability and knowledge sharing.<br>• Take part in peer code review by submitting thoughtful feedback and incorporating suggestions to maintain strong engineering standards.
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.