We are looking for an experienced Data Engineer to strengthen and scale an enterprise data environment in California. This contract opportunity with potential for a permanent role is ideal for someone who enjoys building reliable cloud-based data solutions, shaping reporting-ready datasets, and connecting information from diverse business platforms. The role offers meaningful ownership across data modeling, pipeline development, and analytics enablement while working closely with stakeholders in a collaborative setting.<br><br>Responsibilities:<br>• Create and refine scalable data structures that support reporting, analytics, and long-term platform growth.<br>• Develop and maintain curated datasets that are dependable, well-organized, and ready for business intelligence use.<br>• Connect data from multiple enterprise applications and align it into a consistent, usable format.<br>• Build and manage mappings, reference relationships, and cross-system data associations to improve data consistency.<br>• Enhance existing ingestion and transformation workflows to support expanding business and analytics needs.<br>• Strengthen platform stability through better monitoring, testing practices, and operational improvements.<br>• Tune and optimize data processing performance while contributing to ongoing platform enhancements.<br>• Produce clear documentation for lineage, transformation rules, and support procedures to improve maintainability.<br>• Collaborate with business partners to deliver high-confidence data assets that support reporting and decision-making.<br>• Help establish engineering standards, documentation practices, and technical guidelines across the data platform.
<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>
We are looking for an experienced Data Engineer to join our team in Illinois. This role is suited for a self-directed, technically strong individual who can navigate complex data challenges, influence architectural decisions, and contribute to stronger engineering standards across the team. The ideal candidate brings deep expertise in modern data technologies and a practical approach to building reliable, scalable solutions in a fast-moving environment.<br><br>Responsibilities:<br>• Design, build, and maintain scalable data pipelines that support large-volume processing and analytics needs.<br>• Take ownership of complex engineering initiatives from discovery through delivery, making sound technical decisions with minimal oversight.<br>• Develop and optimize distributed data solutions using technologies such as Apache Spark, Hadoop, and Kafka.<br>• Create robust ETL workflows that ensure data quality, consistency, and availability across multiple systems.<br>• Partner with cross-functional teams to define integration approaches, support API connectivity, and enable dependable data exchange.<br>• Improve system performance through testing, troubleshooting, and targeted optimization of data processing workloads.<br>• Contribute to architecture discussions by recommending effective patterns for scalable, maintainable data platforms.<br>• Support the broader engineering team by sharing knowledge, guiding technical best practices, and helping raise overall delivery quality.
We are looking for a Data Engineer to support healthcare-focused data initiatives in Bridgewater, New Jersey. This Long-term Contract position is ideal for someone who enjoys building reliable data pipelines, working with large-scale datasets, and improving the flow of information across technical environments. The role will contribute to scalable data solutions that help teams access, process, and analyze critical business data efficiently.<br><br>Responsibilities:<br>• Design and maintain scalable data pipelines to collect, transform, and deliver data from multiple sources.<br>• Develop ETL workflows that improve data quality, consistency, and availability for reporting and analytics needs.<br>• Use Python and Apache Spark to process high-volume datasets and optimize performance across data engineering tasks.<br>• Work with Hadoop-based environments to manage distributed data processing and storage effectively.<br>• Integrate streaming and batch data using Apache Kafka to support timely and dependable data movement.<br>• Partner with analysts, developers, and business stakeholders to translate data needs into practical engineering solutions.<br>• Monitor pipeline health, troubleshoot processing issues, and implement improvements that increase reliability and efficiency.
<p>For our client, we are seeking a Data Engineer to design, develop, and maintain scalable data pipelines, integrations, and enterprise data platforms. This individual will work closely with data analysts, architects, and business stakeholders to ensure reliable data ingestion, transformation, storage, and accessibility for reporting, analytics, and business intelligence initiatives.</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 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 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>We are seeking a highly skilled Big Data Engineer to design, build, and optimize scalable data platforms that support enterprise analytics, reporting, machine learning, and business intelligence initiatives. The ideal candidate will have experience developing large-scale data pipelines, managing cloud-based data ecosystems, and implementing high-performance data solutions that enable data-driven decision-making across the organization. Key Responsibilities Design, develop, and maintain large-scale data processing systems and data pipelines. Build and optimize ETL/ELT workflows for structured, semi-structured, and unstructured data sources. Develop scalable solutions using distributed computing frameworks such as Apache Spark, Hadoop, and Kafka. Collaborate with Data Scientists, Analysts, Architects, and business stakeholders to support analytical and operational requirements. Integrate data from multiple internal and external systems while ensuring data quality and integrity. Design and implement cloud-native data solutions within AWS, Azure, or Google Cloud environments. Monitor, troubleshoot, and improve the performance, reliability, and scalability of data platforms. Implement data governance, security, compliance, and access control standards. Support real-time and batch data processing requirements. Document architectures, workflows, and technical specifications to ensure operational excellence.</p>
We are looking for a Data Engineer to strengthen reporting and data capabilities for distribution operations in Minneapolis, Minnesota. In this role, you will turn information from sales, inventory, warehouse, vendor, and point-of-sale platforms into practical insights that support branch leaders, purchasing teams, and senior decision-makers. The position focuses on creating reliable data solutions that improve inventory planning, pricing visibility, and day-to-day operational performance across a multi-site distribution environment.<br><br>Responsibilities:<br>• Design, build, and maintain data pipelines that consolidate information from ERP, point-of-sale, warehouse, vendor, and sales systems.<br>• Develop dashboards and operational reports that help business teams monitor inventory movement, pricing performance, margin trends, and service levels.<br>• Write and optimize SQL queries to extract, validate, and transform data from platforms such as SQL Server, Postgres, and distribution-focused ERP systems.<br>• Partner with branch management, purchasing, and leadership teams to translate business questions into clear analytics and reporting solutions.<br>• Ensure data quality and consistency by investigating discrepancies, validating source data, and improving reporting logic across systems.<br>• Support analysis of inventory health by tracking metrics such as turns, fill rate, reorder thresholds, and safety stock performance.<br>• Produce insights that help identify opportunities to improve replenishment decisions, operational efficiency, and pricing accuracy across multiple branches or warehouses.<br>• Contribute to reporting and integration work involving business systems and connected commerce platforms when operational data needs evolve.
<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>
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.
<p><strong>Data Pipeline Development & Integration</strong></p><ul><li>Design, build, and maintain scalable ETL/ELT pipelines to extract, transform, and load data from multiple sources.</li><li>Develop automated data integration solutions supporting enterprise applications, analytics, and reporting.</li><li>Integrate structured and semi-structured data from APIs, relational databases, cloud platforms, and third-party systems.</li><li>Develop batch and real-time data processing solutions.</li><li>Troubleshoot pipeline failures, data inconsistencies, and performance bottlenecks.</li></ul><p><strong>Data Warehousing & Architecture</strong></p><ul><li>Design and optimize enterprise data warehouses, data lakes, and lakehouse architectures.</li><li>Develop efficient data models, schemas, and transformations to support business intelligence and analytics.</li><li>Build and maintain cloud-based data solutions using AWS, Microsoft Azure, or Google Cloud.</li><li>Optimize SQL queries, database performance, and data processing workloads.</li><li>Implement data partitioning, indexing, and storage optimization strategies.</li></ul><p><strong>Data Quality & Governance</strong></p><ul><li>Develop automated data validation, monitoring, and quality assurance processes.</li><li>Ensure data accuracy, consistency, reliability, and availability across enterprise systems.</li><li>Implement data governance standards, access controls, and security best practices.</li><li>Maintain documentation for data pipelines, architecture, and transformation logic.</li><li>Support compliance with organizational data privacy and security requirements.</li></ul><p><strong>Cloud Engineering & Automation</strong></p><ul><li>Develop and maintain cloud-native data pipelines and processing workflows.</li><li>Utilize orchestration tools such as Apache Airflow, Azure Data Factory, or similar technologies.</li><li>Implement CI/CD practices for data engineering workflows.</li><li>Automate data processing, monitoring, and infrastructure deployment.</li><li>Collaborate with DevOps and infrastructure teams to improve scalability and reliability.</li></ul><p><strong>Analytics & AI Support</strong></p><ul><li>Partner with business intelligence and analytics teams to deliver reliable datasets for reporting and dashboards.</li><li>Develop curated data models supporting Power BI, Tableau, and other visualization platforms.</li><li>Build data pipelines supporting machine learning, predictive analytics, and AI applications.</li><li>Collaborate with AI engineers and data scientists to prepare, transform, and deliver data for model development and production applications.</li><li>Identify opportunities to improve business processes through better data integration and automation.</li></ul><p><br></p><p><br></p>
We are looking for an experienced Data Engineer to support enterprise-scale data initiatives for a financial services environment in Cincinnati, Ohio. This Long-term Contract position will focus on building reliable data foundations, shaping data structures that support investment and portfolio reporting, and partnering with business and technology leaders to solve complex information challenges. The ideal candidate brings deep expertise in modern data engineering, strong knowledge of financial data domains, and the ability to turn strategic needs into scalable technical solutions.<br><br>Responsibilities:<br>• Design and maintain scalable data pipelines that collect, transform, and deliver high-value business and financial data across enterprise platforms.<br>• Develop conceptual, logical, and physical data models that improve consistency, usability, and long-term management of critical information assets.<br>• Collaborate with executive stakeholders, business teams, and technical partners to define data solutions aligned with operational and strategic objectives.<br>• Establish and strengthen practices for data governance, stewardship, metadata management, lineage tracking, and data quality oversight.<br>• Translate complex business questions related to funds, investments, portfolio companies, and investors into effective engineering and data architecture solutions.<br>• Build and optimize ETL workflows using technologies such as Python, Apache Spark, Hadoop, and Kafka to support large-scale data processing.<br>• Partner across business and technology functions to ensure data platforms meet regulatory, privacy, risk, and compliance expectations within a financial services setting.<br>• Analyze enterprise data issues, identify improvement opportunities, and implement solutions that enhance reliability, accessibility, and reporting accuracy.
<p>Robert Half is seeking a <strong>Contract Data Engineer</strong> to support our client’s data and analytics initiatives. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure that enable efficient data ingestion, transformation, and delivery. The ideal candidate has strong experience working with modern data platforms, cloud environments, and large-scale datasets.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><ul><li><strong>Data Pipeline Development:</strong> Design, build, and maintain scalable ETL / ELT pipelines to ingest, transform, and deliver data from multiple sources.</li><li><strong>Data Architecture:</strong> Develop and optimize data models, schemas, and warehouse structures to support analytics, reporting, and business intelligence needs.</li><li><strong>Cloud Data Platforms:</strong> Work within cloud environments such as <strong>AWS, Azure, or GCP</strong> to deploy and manage data solutions.</li><li><strong>Data Warehousing:</strong> Design and support enterprise data warehouses using platforms such as <strong>Snowflake, Redshift, BigQuery, or Azure Synapse</strong>.</li><li><strong>Big Data Processing:</strong> Develop solutions using big data technologies such as <strong>Spark, Databricks, Kafka, and Hadoop</strong> when required.</li><li><strong>Performance Optimization:</strong> Tune queries, pipelines, and storage solutions for performance, scalability, and cost efficiency.</li><li><strong>Data Quality & Reliability:</strong> Implement monitoring, validation, and alerting processes to ensure data accuracy, integrity, and availability.</li><li><strong>Collaboration:</strong> Work closely with Data Analysts, Data Scientists, Software Engineers, and business stakeholders to understand requirements and deliver data solutions.</li><li><strong>Documentation:</strong> Maintain detailed documentation for pipelines, data flows, and system architecture.</li></ul><p><br></p>
We are looking for a Data Engineer to 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.
We are looking for an experienced Data Engineer to join a construction and contractor-focused organization in Appleton, Wisconsin. This contract opportunity with potential for a permanent role is ideal for a senior-level candidate who enjoys building scalable cloud-based data platforms, working hands-on with Python and notebook-driven development, and applying AI-enabled tools to create practical business solutions. The role will focus on designing modern data lake capabilities, improving data movement and transformation processes, and partnering with stakeholders to deliver reliable analytics infrastructure.<br><br>Responsibilities:<br>• Design, build, and enhance modern data lake architecture in Google Cloud Platform to support scalable and efficient data operations.<br>• Develop robust data pipelines using Python, SQL, Spark, and ETL frameworks to ingest, transform, and prepare data from multiple sources.<br>• Create and maintain notebook-based solutions that demonstrate clear technical approaches, reusable logic, and well-documented project outcomes.<br>• Integrate large-scale data processing technologies such as Hadoop and Kafka to support high-volume and streaming data workloads.<br>• Collaborate with cross-functional teams to translate business needs into data engineering solutions that improve reporting, analytics, and operational decision-making.<br>• Apply AI-driven tools and approaches to accelerate development, improve solution quality, and deliver innovative customer-focused outcomes.<br>• Support cloud data environments that may include Azure Data Lake and related platforms as part of broader enterprise data initiatives.<br>• Contribute to data platform improvements, including work connected to enterprise tool adoption or internal platform changes when needed.
We are looking for a Data Engineer to support analytics and data product development for a healthcare-focused team in Florida. This contract opportunity with potential for a permanent role is ideal for someone who enjoys building scalable reporting solutions, creating modern data products, and improving how business users access insights. The role combines hands-on dashboard development with engineering work in Databricks, helping expand advanced analytics capabilities across a lakehouse-based environment.<br><br>Responsibilities:<br>• Design and deliver interactive dashboards and reporting solutions that support business decision-making across the analytics function.<br>• Build and enhance data products within Databricks to provide reliable, user-friendly access to operational and analytical insights.<br>• Develop and maintain ETL pipelines using Python, Apache Spark, and Azure-based data services to prepare data for reporting and analysis.<br>• Create scalable data models and curated datasets in Azure Data Lake and related platforms to support self-service analytics.<br>• Contribute to AI-enabled business intelligence solutions using Databricks tools and lakehouse technologies.<br>• Partner with analytics stakeholders to translate reporting needs into technical solutions that are accurate, efficient, and maintainable.<br>• Support the evolution of reporting assets, including work associated with shifting Power BI-based reporting into Databricks environments.<br>• Monitor data quality, troubleshoot reporting issues, and optimize performance across dashboards, pipelines, and data assets.
We are looking for an experienced Data Engineer to support the design and delivery of scalable data solutions within the People and HR data domain in Philadelphia, Pennsylvania. This Long-term Contract position is ideal for someone who can step into an existing environment, learn source systems quickly, and build reliable data pipelines that support reporting and business analysis. The role centers on hands-on development using Azure Databricks, Spark, and Azure Data Factory, with an emphasis on creating production-ready data assets. Experience working with HR data and workforce-related systems will be highly valuable in helping translate business needs into dependable engineering solutions.<br><br>Responsibilities:<br>• Design, build, and maintain data pipelines that ingest, transform, and prepare HR and workforce data for downstream analytics and reporting.<br>• Develop scalable data processing solutions using Azure Databricks, Python, Spark, and SQL to support production-grade data products.<br>• Orchestrate and monitor data workflows through Azure Data Factory to ensure timely, accurate, and resilient data movement.<br>• Analyze existing data sources and business requirements to create efficient transformation logic and structured datasets.<br>• Collaborate with stakeholders across technical and functional teams to align data engineering deliverables with HR reporting and operational needs.<br>• Improve data quality, performance, and reliability by applying sound ETL practices, validation checks, and optimization techniques.<br>• Support integration efforts involving HR systems and related interfaces, including work connected to evolving source platforms when needed.<br>• Contribute to documentation, technical standards, and knowledge sharing to support maintainability and long-term solution success.
We are looking for a Data Engineer to support healthcare data initiatives for ambulatory operations in Philadelphia, Pennsylvania. This Long-term Contract position will focus on designing and maintaining scalable data pipelines, improving data accessibility, and enabling reliable reporting across clinical and operational environments. The role suits someone who communicates effectively, works well with cross-functional teams, and brings strong experience with modern cloud data platforms and healthcare data systems.<br><br>Responsibilities:<br>• Build and optimize end-to-end data pipelines using Databricks, Snowflake, Azure, and related cloud technologies to support ambulatory operational data needs.<br>• Develop ETL and ELT workflows that ingest, transform, and validate data from healthcare platforms, including Epic Ambulatory and other enterprise sources.<br>• Collaborate with analysts, operational stakeholders, and technical teams to translate business needs into dependable data solutions and well-structured datasets.<br>• Create and maintain data integrations using tools such as Azure Data Factory, Azure Data Lake, Apache Spark, Kafka, Hadoop, and AWS Glue where appropriate.<br>• Ensure data quality, consistency, and performance by monitoring pipeline execution, troubleshooting issues, and implementing scalable engineering practices.<br>• Support the development of a core data engineering function for the team by establishing reusable frameworks, standards, and documentation.<br>• Partner with healthcare and hospital-based stakeholders to deliver data assets that improve operational visibility and decision-making.<br>• Contribute to architecture discussions, code reviews, and process improvements while communicating clearly with both technical and non-technical audiences.
We are looking for a Data Engineer to join a Contract engagement supporting people analytics and HR-focused data initiatives in Philadelphia, Pennsylvania. This role is centered on designing, building, and refining scalable data pipelines and curated data assets using Azure Databricks and Azure Data Factory. The ideal candidate will be comfortable working hands-on with complex source data, translating business needs into reliable transformations, and delivering production-ready solutions with minimal oversight.<br><br>Responsibilities:<br>• Design, build, and maintain robust ETL and ELT workflows that support HR and workforce data products.<br>• Develop scalable data transformations using Python, SQL, Spark, and Azure Databricks to prepare high-quality datasets for downstream use.<br>• Orchestrate and monitor pipeline execution through Azure Data Factory to ensure dependable and timely data delivery.<br>• Analyze existing source systems and data structures to map requirements and create efficient ingestion and transformation logic.<br>• Partner with stakeholders across HR and analytics teams to turn business questions into practical engineering solutions.<br>• Improve data quality, performance, and reliability by applying modern engineering standards, testing practices, and documentation.<br>• Support integrations across HRIS and related platforms, including contributing to interface development where needed.<br>• Create production-ready datasets that enable reporting, workforce analysis, and broader people data initiatives.
We are looking for a Data Engineer to help build and maintain scalable data solutions that support critical business operations within the brokerage industry. This role is based in Chicago, Illinois, and focuses on designing reliable data pipelines, improving data accessibility, and enabling efficient processing across large datasets. The ideal candidate brings strong technical expertise in modern data engineering tools and enjoys working in a fast-paced environment where data quality, performance, and consistency are essential.<br><br>Responsibilities:<br>• Design, develop, and optimize data pipelines that support ingestion, transformation, and delivery of large-scale datasets.<br>• Build and maintain ETL workflows to ensure accurate, timely, and dependable movement of data across platforms.<br>• Use Python and Apache Spark to process complex data efficiently and improve overall pipeline performance.<br>• Work with Apache Hadoop technologies to manage distributed data storage and computation for high-volume workloads.<br>• Implement streaming and messaging solutions with Apache Kafka to support near-real-time data integration needs.<br>• Partner with cross-functional teams to understand data requirements and translate business needs into technical solutions.<br>• Monitor data processes, troubleshoot issues, and resolve bottlenecks to maintain system reliability and data integrity.<br>• Contribute to enhancements involving data platform changes or internal process updates as part of ongoing engineering initiatives.
<p>We are looking for an experienced nCino Developer III to support and advance commercial lending solutions in New Jersey. This long-term contract position is ideal for a detail-oriented individual who combines strong hands-on development capability with Salesforce administration expertise and a solid understanding of lending operations. The role focuses on building reliable, scalable functionality within nCino while partnering with stakeholders to improve workflows, data quality, and platform performance.</p><p><br></p><p>Responsibilities:</p><p>• Develop, maintain, and refine nCino solutions that support commercial lending activities across the organization.</p><p>• Partner with business teams to understand operational needs and convert them into practical technical designs and platform enhancements.</p><p>• Configure and customize nCino and Salesforce features to align system behavior with business processes and user expectations.</p><p>• Monitor and uphold data accuracy, consistency, and security standards across the nCino and Salesforce environments.</p><p>• Investigate platform issues, resolve defects, and provide ongoing support for users relying on nCino-related functionality.</p><p>• Create and manage declarative automation such as flows, approval paths, and assignment logic to improve efficiency and control.</p><p>• Track upcoming nCino and Salesforce releases, assess their impact, and recommend improvements that strengthen platform capabilities.</p><p>• Produce clear technical and process documentation covering configurations, support procedures, and recommended practices.</p><p>• Fulfill assigned compliance obligations, complete required training, and escalate suspicious activity in accordance with applicable regulatory guidelines.</p><p><br></p><p>2710-0013448886</p><p><br></p>
We are looking for a Package Designer to join a growing consumer products organization in West Palm Beach, Florida. This position is ideal for a creative, detail-oriented individual who can translate brand direction into compelling packaging while also managing the technical requirements needed for flawless production. The role combines concept development, production accuracy, and cross-functional coordination to support products launched across retail and ecommerce channels.<br><br>Responsibilities:<br>• Lead packaging assignments from early creative exploration through final approved files and manufacturing handoff.<br>• Create original package designs, visual layouts, and finished artwork for a range of product lines while preserving a consistent brand presence.<br>• Prepare, refine, and adapt dielines, mechanical files, and press-ready assets to align with printer and vendor specifications.<br>• Oversee proofing and prepress activities by checking color, copy, materials, finishes, and sample outputs for quality and accuracy.<br>• Resolve technical or production concerns before manufacturing by identifying risks and recommending practical corrections.<br>• Partner with internal stakeholders, external suppliers, print vendors, and manufacturing teams to keep packaging projects moving on schedule.<br>• Manage updates, artwork revisions, and version control to ensure final deliverables are organized and accurate.<br>• Contribute to related brand, product, and ecommerce creative work when additional design support is needed.
We are looking for an experienced AI Development specialist to contribute to healthcare-focused software initiatives in Wisconsin. This long-term contract opportunity is ideal for an experienced engineer who can lead technical work independently, from solution design through production deployment, while building reliable systems for regulated environments. The role blends modern AI capabilities with backend and API engineering, with a strong emphasis on secure cloud delivery and healthcare data interoperability.<br><br>Responsibilities:<br>• Design, develop, and launch production-grade applications and services that support healthcare technology use cases.<br>• Build and maintain secure cloud-based solutions using AWS, with attention to infrastructure reliability, access controls, and compliance expectations.<br>• Create and evolve external-facing APIs that enable third-party integrations and dependable data exchange.<br>• Work with healthcare interoperability standards such as HL7 and EDI to support clinical and operational data workflows.<br>• Apply strong ownership across the full software lifecycle, including architecture decisions, implementation, testing, deployment, and operational support.<br>• Develop AI-enabled features and integrations using tools such as Claude and OpenAI where they add measurable value to product capabilities.<br>• Implement infrastructure as code practices with tools such as AWS CDK or Terraform to standardize and automate deployment processes.<br>• Collaborate on backend and web application development using modern TypeScript-based frameworks and data platforms.<br>• Support regulated data handling practices in HIPAA-governed environments, including secure storage, encryption, and audit-minded engineering.<br>• Contribute to ongoing evaluation and implementation of database and platform enhancements, including audit, vector, and replication-related capabilities when needed.