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.
<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>
<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 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.
<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 create and enhance scalable data solutions that strengthen business intelligence capabilities across the organization. This role partners with technology leaders, software teams, delivery stakeholders, and external partners to turn business needs into reliable technical outcomes. The position is well suited to someone who thrives in an agile setting, works confidently with minimal supervision, and collaborates effectively across teams. This opportunity is based in Nashville, Tennessee.<br><br>Responsibilities:<br>• Build and refine scalable data pipelines and platform components that support reporting, analytics, and enterprise intelligence initiatives.<br>• Assess modern cloud and big data technologies, gain working knowledge of new tools quickly, and recommend practical options based on business needs.<br>• Translate technical and business requirements into clearly defined tasks, implementation plans, and measurable deliverables.<br>• Write maintainable, efficient, and high-quality code that supports stable and dependable data solutions.<br>• Review existing processes and code for gaps or performance issues, then propose and implement improvements.<br>• Adjust priorities effectively in response to evolving project demands, timelines, and stakeholder expectations.<br>• Take ownership of delivered solutions by documenting design decisions and explaining functionality to team members and partners.<br>• Contribute to additional data engineering efforts that advance organizational goals and strengthen outcomes for end users.
We are looking for a Data Engineer to join a growing team and contribute to the delivery of reliable, analytics-ready data solutions. This contract opportunity with potential for a permanent role is ideal for someone who enjoys building scalable data pipelines, improving data models, and partnering with technical and business stakeholders to support reporting, self-service analytics, and data science. The role offers the chance to work hands-on with Databricks, Python, PySpark, SQL, and modern data engineering practices in a collaborative environment focused on quality and performance.<br><br>Responsibilities:<br>• Build, maintain, and enhance data pipelines that support dependable data availability for analytics and reporting needs.<br>• Collaborate with data engineering leaders to troubleshoot defects, resolve pipeline issues, and improve overall platform stability.<br>• Develop transformation logic using Python, PySpark, SQL, and Databricks to prepare clean, usable datasets for downstream consumers.<br>• Design and refine data models that improve usability, consistency, and performance across reporting and analytical workloads.<br>• Apply layered data architecture principles, including Bronze, Silver, and Gold structures, to organize and manage data effectively.<br>• Establish and follow engineering standards for validation, testing, monitoring, and documentation to strengthen data quality and maintainability.<br>• Optimize processing and query performance to support efficient data delivery at scale.<br>• Work with business and technical partners to translate data needs into practical engineering solutions that support trusted insights.
We are looking for a Data Engineer to join a Financial Services team in Plano, Texas on a contract basis with the potential for a permanent role. This role is focused on designing and delivering reliable data pipelines in a cloud-first environment, with Snowflake serving as a central platform for analytics and data consumption. The position offers a balanced mix of new development and targeted optimization, with an emphasis on improving data quality, operational visibility, and scalable processing capabilities.<br><br>Responsibilities:<br>• Design, build, and deploy end-to-end data pipelines with Snowflake as a primary data platform.<br>• Create new ingestion and transformation workflows while resolving issues affecting existing pipeline performance and reliability.<br>• Support streaming data integration using Apache Kafka to enable timely and scalable data movement.<br>• Strengthen observability across data workflows by improving monitoring, alerting, and pipeline transparency.<br>• Enhance data quality practices through validation, testing, and proactive issue identification.<br>• Modernize data architecture by reducing dependency on legacy processes and addressing technical debt.<br>• Contribute to engineering standards by applying disciplined development practices, code quality measures, and repeatable delivery methods.<br>• Help expand CI/CD and testing capabilities by promoting more consistent automation across build and release activities.<br>• Use AI-assisted development tools to accelerate coding, testing, and documentation where appropriate.
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 a Data Platform Engineer to join a 4-month contract opportunity based in Norman, Oklahoma. This role owns the storage, retention and pipeline-correctness workstream. This is data engineering, not cloud </p><p>infrastructure.</p><p><br></p><p>What they will actually do</p><p>▪ Own the storage and pipeline backlog across the ingestion and processing repositories</p><p>▪ Event ordering and bitemporal modelling: separating event time from ingestion time, deterministic replay</p><p>▪ Atomic snapshot publication with schema admission and rollback</p><p>▪ Design the historical layer on object storage so it can be queried economically and answer as-of </p><p>questions correctly — file format, partitioning, compaction, and whether the canonical layer moves </p><p>onto a managed table format</p><p>▪ Reconcile the operational database and the historical store so a point-in-time question returns one </p><p>answer rather than two</p><p>▪ Evidence immutability and retention: object-lock semantics, preventing overwrite of stored evidence, </p><p>validated recovery paths</p><p>▪ Pipeline durability: idempotent runs, completeness receipts, restore testing</p><p>▪ Support production cutover in month 4 — this seat does not roll off early</p>
We are looking for a Data Engineer to join our Data & Analytics team in Houston, Texas, and help strengthen the reporting foundation that supports decisions across the business. In this role, you will shape data into reliable, business-ready models, develop scalable reporting structures, and work closely with teams such as Finance and Operations to turn complex rules into clear insights. This position blends technical data engineering with analytics-focused development, offering the opportunity to improve reporting quality, maintain dependable data flows, and contribute to ongoing enhancements in our analytics environment.<br><br>Responsibilities:<br>• Develop and maintain structured data models, including staging layers, reporting tables, and dimensional designs within the Azure-based data warehouse environment.<br>• Create and support Power BI semantic models, calculated measures, security configurations, dashboards, and reports used for operational and enterprise reporting.<br>• Monitor scheduled data workflows and dataset refresh activity, investigate processing issues, and resolve failures to keep reporting available and accurate.<br>• Adjust and enhance existing ETL and orchestration processes as business needs evolve, using tools such as Azure Data Factory and related Microsoft data platforms.<br>• Collaborate with stakeholders across functions to translate reporting needs, financial logic, and operational rules into dependable analytical solutions.<br>• Produce clear technical and business documentation covering model design, metric definitions, transformation logic, and data ownership.<br>• Apply and help refine development standards for naming, modeling approach, query design, and reporting structure to improve consistency and quality.<br>• Identify opportunities to streamline current data practices, improve performance, and introduce effective tools or methods that strengthen analytics capabilities.
<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 the 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 practices.</p>
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.
We are looking for an experienced Senior Data Engineer to help design and enhance scalable data platforms that support critical business operations in Houston, Texas. This role is ideal for someone who enjoys building reliable pipelines, improving data accessibility, and working with modern big data technologies in a service-focused environment. The successful candidate will play a key role in shaping data architecture, enabling analytics, and maintaining high standards for performance, quality, and governance.<br><br>Responsibilities:<br>• Design, build, and optimize large-scale data pipelines that collect, transform, and deliver data from multiple sources.<br>• Develop robust ETL workflows using Python and Spark to support reporting, analytics, and operational data needs.<br>• Implement and maintain data solutions across distributed processing environments, including Hadoop and Azure Databricks.<br>• Create streaming and batch data integrations using Kafka and related technologies to ensure timely and dependable data movement.<br>• Collaborate with analysts, engineers, and business stakeholders to translate requirements into scalable technical solutions.<br>• Monitor pipeline performance, troubleshoot data issues, and apply improvements that increase reliability and efficiency.<br>• Establish data quality controls, validation processes, and documentation to support governance and long-term maintainability.<br>• Contribute to platform enhancements and technical initiatives, including changes to data infrastructure or internal processing frameworks when needed.
We are looking for an experienced Lead Data Engineer to oversee the design, implementation, and management of advanced data infrastructure in Houston, Texas. This role requires expertise in architecting scalable solutions, optimizing data pipelines, and ensuring data quality to support analytics, machine learning, and real-time processing. The ideal candidate will have a deep understanding of Lakehouse architecture and Medallion design principles to deliver robust and governed data solutions.<br><br>Responsibilities:<br>• Develop and implement scalable data pipelines to ingest, process, and store large datasets using tools such as Apache Spark, Hadoop, and Kafka.<br>• Utilize cloud platforms like AWS or Azure to manage data storage and processing, leveraging services such as S3, Lambda, and Azure Data Lake.<br>• Design and operationalize data architecture following Medallion patterns to ensure data usability and quality across Bronze, Silver, and Gold layers.<br>• Build and optimize data models and storage solutions, including Databricks Lakehouses, to support analytical and operational needs.<br>• Automate data workflows using tools like Apache Airflow and Fivetran to streamline integration and improve efficiency.<br>• Lead initiatives to establish best practices in data management, facilitating knowledge sharing and collaboration across technical and business teams.<br>• Collaborate with data scientists to provide infrastructure and tools for complex analytical models, using programming languages like Python or R.<br>• Implement and enforce data governance policies, including encryption, masking, and access controls, within cloud environments.<br>• Monitor and troubleshoot data pipelines for performance issues, applying tuning techniques to enhance throughput and reliability.<br>• Stay updated with emerging technologies in data engineering and advocate for improvements to the organization's data systems.
<p>A leading infrastructure and transportation group is seeking a hands-on Senior Data Engineer to architect and build our next-generation Enterprise Reporting & Data Warehouse (ERDW.Next) on Databricks. Acting as the hands-on technical owner, you will drive target-state design, medallion architecture (Delta Lake), and legacy migrations off SQL Server/Synapse while remaining actively in the codebase. You will partner with our Enterprise Architect, Power BI team, business users, and offshore delivery partners across finance, construction, and safety domains.</p><p><br></p><p><strong>QUALIFIED CANDIDATES SHOULD HAVE EXPERIENCE WITH:</strong></p><ul><li>Serving as a Databricks SME</li><li>ERP integrations (strong plus)</li><li>Python / PySpark</li><li>Performance tuning and optimization</li><li>Databricks maintenance, including VACUUM</li><li>Data governance and best practices</li><li>Semantic modeling</li></ul><p><br></p><p><strong>RESPONSIBILITIES</strong></p><ul><li><strong>Architecture & Strategy:</strong> Design the ERDW.Next lakehouse (medallion/gold layer star schema) and govern data modeling, batch/streaming, and Delta Live Tables standards.</li><li><strong>Build & Migration:</strong> Write production-grade PySpark, Spark SQL, and Delta Live Tables pipelines orchestrated via Databricks Workflows. Re-engineer legacy SSIS/T-SQL/Synapse logic and ingest ERP data (JD Edwards, Anaplan) using CDC and Auto Loader.</li><li><strong>Platform Operations:</strong> Optimize cost/performance using Photon, Liquid Clustering, and OPTIMIZE. Manage CI/CD pipelines via Git and Databricks Asset Bundles while maintaining strict SLAs.</li><li><strong>Governance & AI:</strong> Implement Unity Catalog governance (entitlements, lineage, audit) and curate Databricks Genie Agents for natural-language analytics.</li><li><strong>Partner & Legacy Management:</strong> Support legacy platforms during transition and maintain code quality standards across offshore partner teams. Leverage agentic AI coding tools safely to accelerate delivery.</li></ul><p><br></p>
<p>We are looking for a Data Analyst to turn complex healthcare, financial, and operational data into meaningful insights that guide leadership decisions. This position supports organizational performance by connecting information from clinical and business systems, building practical reporting tools, and highlighting trends that matter. Based in Milwaukee, Wisconsin, the role works closely with finance, operations, and clinical stakeholders to improve visibility, planning, and overall effectiveness. <strong><em>Local candidates to the Greater Milwaukee area with Healthcare Epic experience is desired. </em></strong></p><p><br></p><p>Responsibilities:</p><p>• Create and maintain dashboards, scorecards, and recurring reports that combine Epic data with financial and operational information from connected platforms.</p><p>• Work with leaders across finance, operations, and clinical teams to define measurable indicators and track performance in patient services, revenue activity, and resource use.</p><p>• Gather, clean, and evaluate large datasets to support forecasting, monthly business reviews, and long-range planning initiatives.</p><p>• Present findings in a clear, business-focused format so non-technical stakeholders can understand trends, risks, and opportunities.</p><p>• Collaborate with IT and data governance partners to uphold data accuracy, reporting consistency, and compliance with organizational standards.</p><p>• Identify patterns in clinical and administrative workflows and recommend improvements that increase efficiency and support better decision-making.</p><p>• Contribute to reporting automation and process enhancements that improve speed, reliability, and access to timely performance data.</p>
<p><strong>Data & Knowledge Engineer</strong></p><p><br></p><p><strong>Company Overview</strong></p><p>A leading artificial intelligence and advanced analytics organization is seeking a Data & Knowledge Engineer to help power next-generation AI and decision-support platforms. Based in Los Angeles, California, the company specializes in integrating complex data from disparate sources into unified intelligence systems that support advanced analytics, automation, and operational decision-making. This is an opportunity to work on mission-critical initiatives involving large-scale data, knowledge graphs, and AI-driven applications.</p><p><br></p><p><strong>Role Summary</strong></p><p>The Data & Knowledge Engineer will lead the onboarding, transformation, and governance of complex multimodal data into scalable data and knowledge platforms. This role focuses on integrating structured and unstructured data sources, designing reusable data pipelines, developing entity resolution frameworks, and enabling high-quality data for analytics, retrieval, AI workflows, and geospatial applications. The ideal candidate combines strong data engineering expertise with experience in knowledge graphs, data quality, and large-scale information management.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design and develop scalable data ingestion pipelines for structured, unstructured, geospatial, and sensor-based data sources.</li><li>Build and maintain batch and streaming data processing systems across cloud, on-premises, and disconnected environments.</li><li>Develop integrations with APIs, databases, file systems, enterprise applications, and external data sources.</li><li>Design schema mapping, normalization, and transformation processes that support diverse customer data models.</li><li>Implement entity resolution, record linkage, deduplication, and data matching capabilities across multiple sources.</li><li>Preserve data lineage, provenance, auditing, and traceability throughout the data lifecycle.</li><li>Create data validation, monitoring, replay, and exception-handling processes for complex data environments.</li><li>Develop workflows for managing ambiguous records, conflicting information, and data quality issues.</li><li>Define and measure data quality metrics, onboarding effectiveness, and operational performance indicators.</li><li>Support knowledge graph, retrieval, AI, and analytics capabilities through high-quality governed datasets.</li><li>Partner with engineering and stakeholder teams to transform recurring onboarding requirements into reusable platform capabilities.</li><li>Contribute to platform architecture, engineering standards, and long-term data strategy initiatives.</li></ul><p><strong>Additional Details</strong></p><ul><li>Fully onsite 5 days a week</li><li>Full-time exempt position</li><li>Hands-on engineering role with substantial ownership and technical influence</li><li>Opportunity to work on large-scale data, knowledge graph, and AI-driven initiatives</li><li>Staff-level candidates may provide architectural leadership, mentorship, and engineering guidance</li><li>Candidates must be authorized to work in the United States and satisfy applicable regulatory employment requirements</li></ul>
We are looking for a Data Engineer/Modeler to join a long-term contract opportunity in West Des Moines, Iowa. This position focuses on shaping enterprise semantic models and ontology frameworks that make business information consistent, governed, and usable across analytics, reporting, AI, and advanced data initiatives. The ideal candidate will combine strong data modeling expertise with hands-on semantic and knowledge graph experience, along with a solid understanding of insurance data domains. Working closely with technical teams and business partners, this role will help create a trusted data foundation that supports enterprise decision-making.<br><br>Responsibilities:<br>• Build and enhance enterprise ontologies, semantic structures, taxonomies, and knowledge graph models to represent core business concepts in a machine-readable format.<br>• Define entities, attributes, hierarchies, relationships, business rules, and performance metrics across multiple data domains to support a consistent semantic layer.<br>• Develop models for insurance-focused subject areas such as policy, claims, underwriting, customer, product, sales, and producer or agency data.<br>• Translate logic captured in reports, dashboards, operational workflows, stored procedures, and stakeholder knowledge into governed semantic and data models.<br>• Apply both business-led and source-system-driven modeling approaches to align conceptual designs with underlying data structures.<br>• Assess and improve AI-assisted ontology outputs to ensure semantic accuracy, usability, and alignment with enterprise standards.<br>• Connect ontology concepts to physical source systems and confirm model integrity against trusted systems of record.<br>• Manage model promotion and version control across development, testing, and production environments using Git and established release practices.<br>• Partner with architects, engineers, BI teams, analysts, and business stakeholders to deliver scalable semantic solutions and support governance, lineage, metadata, and data quality efforts.
We are looking for a skilled Database Engineer to join our team in Westlake, Ohio. In this role, you will design, implement, and optimize database solutions to support business operations and data-driven decision-making. You will collaborate with cross-functional teams and leverage advanced technologies to ensure robust database performance and scalability.<br><br>Responsibilities:<br>• Design and implement database solutions that align with business requirements and technical specifications.<br>• Optimize and tune database performance to ensure efficiency and scalability.<br>• Collaborate with cross-functional teams to analyze data needs and develop appropriate solutions.<br>• Write, test, and troubleshoot complex SQL queries, including joins, aggregations, and stored procedures.<br>• Monitor and maintain database systems, performing regular updates and performance checks.<br>• Utilize source control and CI/CD tools, such as Azure DevOps, to manage database development and deployment.<br>• Stay updated on emerging technologies and integrate new tools into existing systems as needed.<br>• Provide technical guidance and support to team members regarding database-related issues.<br>• Ensure data integrity and security through regular audits and implementation of best practices.
<p>**** For Faster response on the position, please send a message to Jimmy Escobar on LinkedIn or send an email to Jimmy.Escobar@roberthalf(.com) with your resume.****</p><p><br></p><p>We are looking for a Principal Product Manager to guide the direction of a workforce-focused product serving healthcare organizations in San Diego, California. This Long-term Contract position will shape strategy by connecting customer needs, operational realities, and measurable business outcomes across staffing, finance, HR, and clinical leadership. The ideal candidate brings strong product judgment, a deep understanding of workforce-related challenges, and the ability to turn complex insights into a clear product path that delivers meaningful value.</p><p><br></p><p>Responsibilities:</p><p>• Lead product direction by ensuring the team focuses on meaningful customer and business problems rather than feature delivery alone.</p><p>• Build a strong understanding of workforce planning, staffing operations, nursing leadership, finance, HR, and vendor management to inform product decisions.</p><p>• Convert customer pain points, market opportunities, and desired outcomes into a practical product strategy and sequencing approach.</p><p>• Evaluate and prioritize high-impact opportunities such as unified data visibility, confidence in staffing data, demand forecasting insight, supply optimization, guided decision support, cost control, workflow collaboration, and compliance support.</p><p>• Define and track success measures tied to business impact, including staffing efficiency, labor cost reduction, internal fill improvement, forecasting adoption, and confidence in workforce data.</p><p>• Partner with cross-functional stakeholders across operations, finance, IT, legal, compliance, and leadership to align on direction while maintaining focus on user needs and outcomes.</p><p>• Use discovery methods such as interviews, assumption testing, prototype evaluation, concierge testing, and business-case analysis before committing to complex product investments.</p><p>• Apply data fluency to challenge inconsistent metric definitions and clarify how key workforce measures are interpreted across teams and facilities.</p><p>• Make informed prioritization decisions in ambiguous situations and identify the best entry point for product adoption and value creation.</p><p>• Connect product performance indicators to broader organizational results such as reduced agency spend, lower avoidable overtime, faster staffing gap resolution, and less manual reconciliation effort.</p>
We are looking for an experienced Power BI Business Intelligence Engineer to join our team in Niceville, Florida. In this role, you will play a vital part in managing and enhancing our reporting and business intelligence platforms to provide actionable insights. Your expertise will drive data analysis, dashboard creation, and the development of solutions that support key business decisions.<br><br>Responsibilities:<br>• Oversee the company's reporting and business intelligence systems to ensure optimal performance and accuracy.<br>• Develop a deep understanding of the organization's business models, operations, and decision-making processes.<br>• Analyze data architecture and gather requirements from stakeholders to create tailored solutions.<br>• Build and manage data sources, models, and integrations for reporting and analytics purposes.<br>• Design and maintain dashboards and reports using enterprise business intelligence tools.<br>• Facilitate seamless data integration processes to retrieve, transform, and analyze datasets.<br>• Support leadership in creating management information and KPIs to drive data-driven decision-making.<br>• Ensure data quality and integrity across all business intelligence deliverables.<br>• Stay updated with the latest advancements in BI technologies, tools, and practices to recommend improvements.<br>• Document systems and processes comprehensively while adhering to governance, security, and privacy standards.
We are looking for a Senior Data Engineer to help shape and expand a modern enterprise data ecosystem in Dallas, Texas. This role is ideal for a highly technical specialist who enjoys building scalable cloud-based data solutions, improving platform performance, and collaborating with both engineering and business leaders. The position offers the opportunity to contribute directly to lakehouse design, advanced pipeline development, and data initiatives that support analytics and emerging AI use cases.<br><br>Responsibilities:<br>• Architect and develop scalable data platforms using Azure Databricks, Spark, PySpark, Python, Delta Lake, and related big data technologies.<br>• Create and maintain layered lakehouse data models across raw, refined, and curated environments to support enterprise reporting and analytics.<br>• Lead the movement of legacy data assets into Azure-based cloud environments as part of broader platform modernization efforts.<br>• Build, enhance, and monitor high-volume ETL and streaming workflows, notebooks, and distributed processing jobs for reliability and efficiency.<br>• Integrate tools such as Azure Synapse Analytics and Azure Data Factory to support end-to-end data ingestion, transformation, and delivery.<br>• Improve performance of large-scale data workloads by tuning Spark jobs, optimizing code, and applying engineering best practices.<br>• Establish and follow modern software delivery standards through source control, Azure DevOps pipelines, CI/CD processes, and deployment automation.<br>• Prepare and structure data for machine learning, generative AI, and MLOps initiatives, including feature creation and production-ready integration.<br>• Work closely with implementation partners, architects, technical teams, business stakeholders, and senior leadership to align solutions with organizational goals.<br>• Contribute hands-on engineering expertise while also helping guide technical design and platform architecture decisions.
<p>Join a growing data team focused on building enterprise-grade data pipelines and analytics platforms. You'll work with modern cloud technologies and help drive data-driven decision-making.</p><p>Responsibilities</p><ul><li>Develop and maintain ETL/ELT processes</li><li>Design dimensional data models and data warehouses</li><li>Build integrations with APIs and enterprise systems</li><li>Optimize SQL queries and data processing jobs</li><li>Support reporting and business intelligence initiatives</li><li>Maintain data quality and governance standards</li></ul><p><br></p>
We are looking for a Data Scientist to join a healthcare-focused analytics team in Texas, where you will turn complex data into practical insights and scalable solutions. This contract position with the potential to become permanent is ideal for someone who combines strong statistical knowledge with curiosity, business acumen, and a passion for solving meaningful problems. You will work closely with technical and business partners to design predictive models, improve data quality, and communicate findings that support informed decision-making.<br><br>Responsibilities:<br>• Transform large, complex datasets into actionable insights by exploring trends, identifying patterns, and uncovering opportunities that support business goals.<br>• Build, test, and refine machine learning models and predictive solutions that improve decision-making and deliver measurable value.<br>• Prepare structured and unstructured data for analysis through cleansing, validation, and preprocessing to ensure reliability and usability.<br>• Strengthen data acquisition practices by recommending improvements that capture the information needed for advanced analytics initiatives.<br>• Partner with business leaders, analysts, and IT teams to define problems, evaluate options, and shape data-driven strategies.<br>• Communicate analytical findings through clear narratives, presentations, and visualizations that make complex results easy to understand.<br>• Create impactful dashboards and visual tools that highlight performance gaps, emerging opportunities, and areas for operational improvement.<br>• Facilitate discussions with stakeholders to gather requirements, iterate on analytical approaches, and align solutions with business needs.<br>• Handle sensitive information with discretion while supporting a culture of continuous improvement, accountability, and evidence-based decision-making.