We are looking for a Data Scientist to join our team in Jacksonville, Florida, and deliver advanced analytics solutions that support decision-making in a financial services environment. In this role, you will transform complex data into scalable models, actionable insights, and clear visual narratives for business and technical partners. The ideal candidate brings strong experience across machine learning, big data platforms, and model deployment, along with the ability to turn exploratory concepts into production-ready solutions.<br><br>Responsibilities:<br>• Build, validate, and implement machine learning and predictive analytics solutions that address business needs within banking, payments, or financial services use cases.<br>• Prepare and refine large, complex datasets by performing data cleaning, transformation, and feature development to improve model performance and reliability.<br>• Develop analytical models using statistical and machine learning techniques such as classification, clustering, ensemble methods, and other predictive approaches.<br>• Work with big data tools and distributed processing frameworks to analyze high-volume datasets efficiently and support scalable model development.<br>• Create dashboards, visual reports, and data stories that communicate findings and recommendations to both technical teams and business stakeholders.<br>• Use Databricks capabilities such as collaborative notebooks, experiment tracking, model management, and automated workflows to support end-to-end model development.<br>• Design proof-of-concept initiatives that explore new opportunities, assess business value, and guide the expansion of successful solutions into broader use.<br>• Apply natural language processing methods where appropriate to extract insight from unstructured information and solve business problems.<br>• Partner with cross-functional teams to deploy, monitor, and maintain production-ready models in alignment with governance and operational expectations.
We are looking for a Data Scientist to support advanced analytics and machine learning initiatives in Sacramento, California. This Long-term Contract position focuses on creating practical, production-ready solutions that improve operational decision-making, with an early emphasis on predictive maintenance and fleet performance in asset-heavy environments. The role works closely with business leaders and technical teams to turn complex data into reliable models, useful insights, and scalable AI capabilities.<br><br>Responsibilities:<br>• Build, test, and implement machine learning and analytical models using operational, maintenance, and telemetry data to improve equipment reliability and reduce unexpected downtime.<br>• Create pilot solutions with measurable success criteria, then develop high-performing concepts into stable model pipelines suitable for ongoing production use.<br>• Convert analytical results into clear recommendations, dashboards, or decision-support outputs that help both technical teams and business stakeholders act with confidence.<br>• Partner with data engineering teams to shape requirements for data intake, transformation, feature creation, and model delivery across the broader data environment.<br>• Document methodologies, assumptions, dependencies, and performance results to support transparency, repeatability, and effective model governance.<br>• Provide input on enterprise data architecture needs from a data science perspective, including dataset design, feature availability, experiment tracking, and model readiness.<br>• Identify data limitations, quality concerns, and enrichment opportunities that could influence model accuracy or business value.<br>• Work with cross-functional partners to define new analytics and AI opportunities and assess external tools or vendor-developed solutions when needed.
We are looking for an experienced Data Security Analyst to join our team on a Contract basis. This role is suited for a self-directed, detail-oriented individual who can contribute immediately by leading security and compliance assessments across several client engagements at once. The ideal candidate brings strong judgment in evaluating control environments, interpreting evidence, and producing clear assessment documentation in fast-paced consulting settings.<br><br>Responsibilities:<br>• Lead data security and compliance assessments for multiple client projects running in parallel.<br>• Examine technical and administrative controls by analyzing policies, procedures, system settings, and other supporting documentation.<br>• Determine whether client environments align with applicable compliance obligations and note areas requiring improvement.<br>• Record observations, conclusions, and supporting materials accurately within Fieldguide or a similar assessment platform.<br>• Partner with assessment leads and client stakeholders to collect information and confirm how controls are designed and operating.<br>• Communicate progress, emerging risks, and key findings during internal status discussions and project checkpoints.<br>• Manage deadlines across concurrent engagements while maintaining consistent quality and attention to detail.<br>• Prepare assessment deliverables for manager review and incorporate feedback to support final quality assurance.
We are looking for an IT Financial Analyst to join a team in South Haven, Minnesota on a Long-term Contract basis. This opportunity is well suited for someone who enjoys working with detailed information, improving data quality, and supporting reliable reporting across business systems. The role focuses on maintaining accurate records, reviewing imported information, and partnering with cross-functional teams to keep data aligned with operational needs.<br><br>Responsibilities:<br>• Transfer and reconcile engineering and manufacturing data across multiple business applications, including spreadsheets and enterprise systems.<br>• Examine uploaded records to confirm completeness, accuracy, and consistency before information is finalized.<br>• Investigate mismatched or incomplete data, correct routine issues, and escalate more complex problems to the appropriate technical or engineering teams.<br>• Validate key production details such as part identifiers, material specifications, counts, and related item information.<br>• Keep thorough records of completed updates, corrections made, and exceptions identified during data review activities.<br>• Support dependable information flow between connected systems by following established controls and quality standards.<br>• Collaborate with engineering, drafting, manufacturing, and IT stakeholders during system-related process updates and data activities.<br>• Contribute to the development of data entry methods, workflow guidance, and documentation as procedures evolve.<br>• Participate in testing revised processes, documenting outcomes, and assisting with ongoing data cleanup or special assignments as needed.
We are looking for a Data Solutions Engineer to support retail data initiatives in Minnesota. This long-term contract opportunity is suited for a hands-on data specialist who can shape scalable data solutions, strengthen reporting capabilities, and guide technical teams toward reliable delivery. The role combines data engineering, business intelligence, and stakeholder collaboration to create trusted data assets that support operational and strategic decision-making.<br><br>Responsibilities:<br>• Guide and support data engineering and BI team members by setting direction, encouraging growth, and promoting strong cross-functional collaboration.<br>• Translate business priorities into measurable delivery goals, establish performance indicators, and monitor progress against expected outcomes.<br>• Architect, develop, and maintain robust data pipelines that move and transform information across internal platforms and third-party sources.<br>• Oversee ETL operations to ensure data is accurate, timely, and dependable for downstream reporting and analytics needs.<br>• Build and refine data models and warehouse structures that enable reporting, advanced analytics, and future predictive or machine learning use cases.<br>• Apply sound engineering practices such as automation, source control, and repeatable development standards to improve data platform quality and efficiency.<br>• Lead the creation and enhancement of Power BI and SSRS reporting solutions with a focus on usability, consistency, and alignment with business objectives.<br>• Partner with business stakeholders to gather requirements, convert them into technical designs, and deliver scalable BI and data solutions.<br>• Define visualization standards, reusable datasets, and semantic layers that support self-service reporting across the organization.
<p>Our client is seeking a Data Scientist II – Generative AI to join a cutting-edge team focused on building scalable, production-ready AI solutions that transform business workflows and deliver measurable impact across global operations. This role is ideal for professionals passionate about leveraging Generative AI technologies, creating intelligent agents, and driving innovation at scale.</p><p><br></p><p>You will design and implement GenAI-powered agents that streamline internal processes, enhance productivity, and support business development initiatives. Responsibilities include developing robust prompt engineering frameworks, building RAG pipelines, and converting prototypes into production-ready solutions. You’ll collaborate closely with engineering and business teams to ensure solutions meet diverse client needs and are optimized for global deployment.</p><p><br></p><p>Key projects include extending the company’s GPT platform, creating AI agents that improve efficiencies for RFP development, onboarding materials, and SOW requirements. Success in this role means quickly ramping up on backlog projects, delivering high-priority initiatives, and staying ahead of emerging GenAI frameworks to continuously advance internal AI capabilities.</p>
<p>We are looking for a Data Analyst / CDP Developer to join a great organization in Southern California. This Long-term Contract position focuses on transforming customer data into reliable insights, strengthening platform performance, and supporting data-driven decisions across cross-functional teams. The role is ideal for someone who combines strong analytical thinking with hands-on development skills in SQL, Python, and cloud-based data environments. You will work onsite four days per week while partnering with technical and business stakeholders to improve data quality, workflow stability, and reporting accuracy.</p><p><br></p><p>Responsibilities:</p><p>• Examine customer event data and other high-volume datasets to uncover trends, confirm data integrity, and support informed business decisions.</p><p>• Develop, refine, and maintain complex queries across distributed data platforms such as Presto, Hive, and NoSQL environments.</p><p>• Use Python to streamline data processing, automate recurring tasks, and support platform integrations and operational workflows.</p><p>• Partner with engineering, analytics, marketing, and subject matter experts to gather requirements, validate outputs, and align solutions with business needs.</p><p>• Monitor and manage scheduled pipelines and workflow orchestration processes, resolving failures and improving overall job reliability.</p><p>• Perform investigative analysis to identify anomalies, test assumptions, and troubleshoot issues affecting data ingestion, transformation, and delivery.</p><p>• Strengthen data quality practices by implementing validation checks, alerts, and monitoring approaches that improve observability in production environments.</p><p>• Create clear documentation for data logic, business rules, workflows, issue resolution, and preventive actions using Confluence or similar tools.</p><p>• Apply version control and CI/CD standards to data scripts and related assets while helping maintain consistent development best practices.</p><p>• Ensure data handling activities follow privacy, compliance, and governance expectations when working with customer-level and production information.</p>
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 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 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.
<p>We are looking for an experienced Data Engineer to jcreate and enhance dependable data platforms that support HR and enterprise analytics, partnering closely with analysts, engineering leads, and business stakeholders on site. The position focuses on building scalable pipelines, strengthening data quality, and enabling trusted insights that improve operational decision-making across the organization.</p><p><br></p><p>Responsibilities:</p><p>• Design, develop, and maintain scalable data pipelines that integrate information from files, APIs, databases, replicated sources, and streaming inputs.</p><p>• Build and support modern data environments across warehouses, data lakes, and lakehouse architectures to meet analytics and reporting needs.</p><p>• Partner with business analysts, HR stakeholders, and technical team members to translate data requirements into reliable engineering solutions.</p><p>• Improve data quality, lineage, and governance by applying metadata-driven practices and implementing controls that increase trust in enterprise datasets.</p><p>• Lead end-to-end delivery of data engineering initiatives, from solution design and development through testing, deployment, and operational support.</p><p>• Manage orchestration, scheduling, and monitoring of data workflows to ensure stable performance and timely delivery of critical datasets.</p><p>• Apply DevOps practices such as version control, automated testing, and CI/CD processes to increase deployment quality and team collaboration.</p><p>• Use Python, SQL, and cloud-based tools to automate data processing, optimize performance, and support scalable distributed workloads.</p><p>• Implement data protection measures, including masking, encryption, anonymization, and role-aware access design, especially for sensitive workforce information.</p><p>• Support curated analytical datasets and reporting solutions by collaborating with downstream users on trusted models and enterprise data products.</p>
We are looking for a Data Engineer to help design and enhance data solutions that support reliable reporting and analytics in Salt Lake City, Utah. This role focuses on building scalable data pipelines, shaping well-structured warehouse models, and improving the quality and usability of enterprise data assets. The ideal candidate brings strong experience with SQL, Python, AWS technologies, and dimensional modeling principles grounded in the Kimball methodology.<br><br>Responsibilities:<br>• Build and maintain data pipelines that ingest, transform, and prepare information for downstream analytics and business use.<br>• Design warehouse structures using Kimball-based dimensional modeling practices to support clear, consistent reporting.<br>• Develop and optimize SQL- and Python-driven data workflows with an emphasis on scalability, performance, and maintainability.<br>• Partner with analysts, engineers, and business stakeholders to translate data needs into practical engineering solutions.<br>• Create and manage data transformation logic using dbt to improve testing, documentation, and deployment consistency.<br>• Support cloud-based data platforms in an AWS environment and contribute to ongoing improvements in data architecture.<br>• Monitor data quality and troubleshoot pipeline issues to ensure dependable delivery of curated datasets.<br>• Contribute to modern data engineering practices, including tools such as PySpark when needed for larger-scale processing.
<p><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 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 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 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.
<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 support scalable data solutions for a Long-term Contract position based in Cincinnati, Ohio. This role focuses on building reliable data pipelines, optimizing data movement across platforms, and enabling efficient access to high-quality datasets for business and technical teams. The ideal candidate brings strong hands-on experience with modern big data tools and a practical approach to designing robust ETL workflows.<br><br>Responsibilities:<br>• Design and maintain end-to-end data pipelines that process large and complex datasets with a focus on performance and reliability.<br>• Develop ETL workflows using Python and Spark to transform raw data into structured, usable formats for downstream consumption.<br>• Work with Hadoop-based environments to manage distributed data processing and storage activities at scale.<br>• Integrate streaming and messaging components such as Kafka to support near real-time data ingestion and event-driven processing.<br>• Monitor pipeline health, troubleshoot data issues, and implement improvements that strengthen stability and data quality.<br>• Collaborate with analysts, developers, and other stakeholders to understand data needs and translate them into technical solutions.<br>• Improve existing data architecture by refining workflows, reducing processing bottlenecks, and increasing operational efficiency.
We are looking for a Data Engineer to support scalable data solutions for a long-term contract opportunity in The Woodlands, Texas. This role focuses on designing and optimizing data pipelines, integrating large-scale data sources, and enabling reliable access to critical business information. The ideal candidate will bring strong hands-on experience with modern big data technologies and a practical approach to building efficient ETL workflows.<br><br>Responsibilities:<br>• Build, maintain, and enhance robust data pipelines to process large volumes of structured and unstructured information.<br>• Develop ETL workflows that transform raw data into reliable datasets for analytics, reporting, and operational use.<br>• Use Python and Apache Spark to engineer high-performance data processing solutions across distributed environments.<br>• Work with Apache Hadoop ecosystems to manage storage and support scalable data operations.<br>• Integrate streaming and event-driven data using Apache Kafka to improve data availability and timeliness.<br>• Monitor data workflows, troubleshoot processing issues, and implement improvements that increase reliability and efficiency.<br>• Collaborate with technical and business stakeholders to understand data needs and translate them into practical engineering solutions.<br>• Document pipeline architecture, data flow logic, and operational procedures to support maintainability and team knowledge sharing.
We are looking for a Data Engineer to 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 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 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><strong>Robert Half</strong> is actively partnering with an Austin-based client to identify a Data Engineer <strong>(contract).</strong> In this role, you will provide both technical and project leadership in designing, developing, and optimizing modern data solutions. This role will partner closely with business and technology stakeholders to deliver scalable data pipelines, drive data strategy initiatives, and lead cross-functional teams in a fast-paced enterprise environment. <strong>This role is hybrid in Austin, Tx. </strong></p><p><br></p><p><strong>Key Responsibilities:</strong></p><ul><li>Lead the design, development, and delivery of enterprise data engineering and integration initiatives.</li><li>Partner with business stakeholders to gather requirements, define solutions, and ensure successful project execution.</li><li>Drive Agile delivery practices while supporting strategic business priorities and innovation initiatives.</li><li>Architect, build, and optimize scalable data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.</li><li>Develop and maintain robust ETL/ELT processes to integrate data from multiple enterprise systems and external sources.</li><li>Implement data quality controls, validation processes, and monitoring frameworks to ensure data accuracy and reliability.</li><li>Mentor and guide junior engineers, fostering technical growth and supporting team success.</li><li>Establish and maintain data security, governance, and access control standards.</li><li>Collaborate with product owners, engineering teams, analysts, QA, operations, and project stakeholders to deliver high-quality solutions.</li><li>Translate business requirements into technical specifications, data mappings, and implementation plans.</li><li>Identify project risks, dependencies, and technical challenges while developing mitigation strategies.</li><li>Create and maintain documentation for deployments, support procedures, and operational processes.</li><li>Support deployment automation, application support efforts, and continuous process improvement initiatives.</li><li>Coordinate with distributed teams across multiple locations and time zones to drive successful project outcomes.</li></ul>
<p>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>