<p>Lead Data Engineer</p><p>Salary: Up to $160,000 Location:</p><p>On-Site | South Los Angeles Area</p><p>Employment Type: Full-Time</p><p><br></p><p>Build the Foundation for Enterprise Analytics</p><p><br></p><p>We are seeking a Lead Data Engineer to drive the architecture, modernization, and expansion of a growing enterprise data platform built within the Microsoft Azure ecosystem. This is a highly visible technical leadership role where you'll help shape the future of data across multiple business functions by building scalable, secure, and high-performing data solutions.</p><p><br></p><p>If you're passionate about Databricks, cloud data platforms, and mentoring engineering teams while remaining hands-on with development, this is an opportunity to make a significant impact.</p><p><br></p><p>What You'll Do</p><ul><li>Lead the design, implementation, and optimization of an enterprise Azure Databricks Lakehouse environment utilizing Bronze, Silver, and Gold data layers.</li><li>Architect and execute migrations from SQL Server and legacy platforms into modern cloud-native data solutions.</li><li>Develop and optimize large-scale ETL/ELT pipelines supporting operational reporting, business intelligence, advanced analytics, and data science initiatives.</li><li>Integrate data from multiple enterprise systems, APIs, operational platforms, and third-party sources.</li><li>Establish best practices for data engineering, data modeling, testing, CI/CD, monitoring, governance, and production support.</li><li>Implement and maintain data governance frameworks, security controls, lineage tracking, and access management.</li><li>Lead code reviews, technical design discussions, and engineering standards across the data team.</li><li>Mentor and support data engineers while fostering a culture of technical excellence.</li><li>Partner closely with business stakeholders, analysts, and data scientists to deliver trusted, scalable data products.</li></ul><p>For immediate consideration, apply now and direct message Reid Gormly on LINKEDIN</p>
<p><strong>Lead Data Engineer</strong></p><p><br></p><p><strong>Company Overview</strong> </p><p>A media organization is seeking a Lead Data Engineer to support enterprise data, analytics, and emerging technology initiatives. This role offers the opportunity to lead technical projects, mentor engineers, and help shape the organization's data strategy.</p><p><br></p><p><strong>Role Summary</strong> </p><p>The Lead Data Engineer will be a hands-on technical leader responsible for data engineering, analytics, automation, and AI-related initiatives. This role combines individual contribution, technical direction, team mentorship, and cross-functional collaboration.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Lead the design, development, and support of enterprise data solutions.</li><li>Provide technical leadership and establish development best practices.</li><li>Oversee data pipelines, integrations, reporting, and automation initiatives.</li><li>Partner with business and technology stakeholders to prioritize work and deliver solutions.</li><li>Monitor data quality, reliability, and operational performance.</li><li>Mentor team members and support their technical development.</li><li>Evaluate emerging technologies and identify opportunities for innovation.</li></ul>
<p>We are looking for a Data Engineer to support data-driven initiatives for a services environment in Southern California. This Long-term Contract position focuses on building reliable data pipelines, improving data availability, and enabling scalable processing for analytics and operational needs. The ideal candidate brings strong hands-on experience with modern data engineering tools and can work across large data sets with accuracy and efficiency.</p><p><br></p><p><strong>Role :</strong></p><ul><li>Design, develop, maintain, and optimize business intelligence solutions, ETL workflows, reporting systems, and data integration processes.</li><li>Collaborate with business, analytics, and technical teams to gather requirements and deliver reporting and analytics solutions.</li><li>Develop and maintain data models, SQL scripts, stored procedures, dashboards, and reporting solutions.</li><li>Build, optimize, and support ETL pipelines across on-premises and cloud environments.</li><li>Troubleshoot and resolve complex reporting, data quality, performance, and integration issues.</li><li>Validate reporting logic, data transformations, and reporting accuracy.</li><li>Perform performance tuning for SQL queries, stored procedures, ETL workflows, and reporting platforms.</li><li>Participate in architecture discussions and provide technical recommendations aligned with business objectives.</li><li>Create and maintain technical documentation including solution designs, data mappings, and operational procedures.</li><li>Participate in code reviews and enforce development, reporting, and data governance standards.</li><li>Mentor junior developers through technical guidance and knowledge-sharing activities.</li><li>Support Agile delivery activities including sprint planning, backlog refinement, and project execution.</li><li>Collaborate with stakeholders and leadership teams to support business intelligence initiatives.</li><li>Drive continuous improvement initiatives related to reporting quality, analytics performance, and operational efficiency.</li></ul><p><br></p><p><br></p><p><br></p>
<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>
<p>We are seeking an experienced <strong>Data Engineer</strong> to architect, build, and optimize scalable data pipelines and cloud-based data platforms that support advanced analytics, reporting, and business intelligence initiatives.</p><p><strong>Responsibilities</strong></p><ul><li>Design, develop, and maintain robust ETL/ELT pipelines for ingesting, transforming, and loading structured and semi-structured data.</li><li>Build and manage scalable data pipelines using <strong>Python</strong> and <strong>SQL</strong> across cloud and warehouse environments.</li><li>Optimize data storage, query performance, and overall efficiency within modern data warehouse platforms.</li><li>Develop and maintain data models that support downstream analytics, reporting, and operational use cases.</li><li>Collaborate with business stakeholders, analysts, and engineering teams to define data requirements and translate them into technical solutions.</li><li>Implement and support data quality checks, governance standards, and monitoring processes to ensure data reliability and integrity.</li><li>Troubleshoot pipeline failures, performance bottlenecks, and data consistency issues across the data ecosystem.</li><li>Contribute to best practices in data architecture, orchestration, documentation, and deployment.</li></ul><p><br></p>
<p>We are looking for a Data Engineer to help shape and strengthen the organization’s data warehouse and analytics capabilities. This role will focus on building reliable data solutions that support reporting, business intelligence, and operational decision-making across the company. The ideal candidate brings strong technical depth in data engineering, enjoys solving complex integration challenges, and works effectively with both IT colleagues and business stakeholders.</p><p><br></p><p>Responsibilities:</p><p>• Design and enhance scalable data warehouse structures and integration pipelines that support analytics, reporting, and cross-system data flow.</p><p>• Develop, test, and maintain ETL processes that move data from varied source systems into staging, warehouse, and downstream reporting environments.</p><p>• Partner with business teams and technical peers to translate functional needs into practical data solutions and system designs.</p><p>• Improve database performance by tuning SQL, refining indexing strategies, and addressing issues identified through execution plan analysis.</p><p>• Create and support dashboards, reports, and data visualizations using tools such as Power BI, Tableau, and similar business intelligence platforms.</p><p>• Perform data validation, auditing, and quality checks to protect accuracy, consistency, and compliance across critical datasets.</p><p>• Provide production support for data platforms, integrations, and reporting solutions, resolving issues and maintaining dependable system performance.</p><p>• Contribute to agile delivery efforts by participating in development, testing, and quality assurance activities across databases, middleware, and analytics applications</p>
<p>The Data Engineer will develop and maintain scalable data pipelines and cloud-based data solutions that support analytics and business intelligence initiatives.</p><p>Responsibilities</p><ul><li>Design and build ETL/ELT processes.</li><li>Develop data pipelines using Python and SQL.</li><li>Optimize data warehouse performance.</li><li>Work with stakeholders to gather data requirements.</li><li>Support data governance and quality initiatives.</li></ul><p><br></p>
We are looking for an experienced Data Engineer for a permanent opportunity in Northern, Virginia. In this role, you will design reliable data solutions that support analytics and business decision-making while helping improve the overall data environment. The ideal candidate brings strong technical depth in modern data engineering practices and enjoys building scalable systems from the ground up. <br> Responsibilities: • Design, develop, and maintain robust data pipelines that collect, transform, and deliver high-quality data for reporting and analysis. • Create and optimize data models that support business intelligence, analytics, and operational use cases across the organization. • Build and manage ETL workflows using Python and related technologies to ensure efficient movement of data between systems. • Work with large-scale data processing tools such as Apache Spark and Hadoop to handle complex and high-volume datasets. • Integrate streaming and batch data sources using technologies such as Apache Kafka to support timely and reliable data availability. • Collaborate with analysts, engineers, and business stakeholders to translate data needs into scalable engineering solutions. • Improve data warehouse performance, structure, and reliability to support accurate and accessible enterprise data. • Use dbt and other modern data transformation practices to organize, test, and document datasets effectively.
<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>
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 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 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 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.
<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>
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.
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 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 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>We are looking for a Principal Data Engineer to shape and lead a modern enterprise data platform serving multiple business lines. This position will define the architectural direction for a Microsoft Fabric-based environment, guide engineering best practices, and partner closely with data and IT leaders to support long-term growth. The role is ideal for a senior technical expert who combines deep hands-on engineering capability with strong mentorship and platform strategy experience.</p><p><br></p><p>Responsibilities:</p><p>• Lead the design and ongoing evolution of a Microsoft Fabric lakehouse environment, establishing a scalable architecture across raw, refined, and curated data layers.</p><p>• Create and support robust data integration workflows that bring information together from more than 30 enterprise applications and operational platforms.</p><p>• Set technical standards for data engineering, including coding practices, solution design patterns, documentation, and review processes.</p><p>• Mentor data engineers through hands-on coaching, collaborative development, and detailed code feedback to strengthen team capability.</p><p>• Partner with data and IT leadership to align platform architecture with business priorities and future expansion needs.</p><p>• Develop high-quality data pipelines using modern tools and frameworks such as SQL, Python, Spark, and PySpark within cloud-based data ecosystems.</p><p>• Evaluate new technologies, architectural approaches, and data platform trends, then provide informed recommendations for adoption.</p><p>• Support governance and platform reliability by promoting strong lineage, quality, performance, and scalable engineering practices.</p><p>• Contribute to cross-platform interoperability initiatives, including environments that may involve Databricks, governance tooling, and enterprise data services.</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.
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.
<p>We are looking for a Data Engineer to join a Chemicals Manufacturing organization in New Jersey in a contract-to-permanent capacity. This role focuses on creating reliable, secure, and scalable data solutions that connect operational and business systems to enterprise reporting, analytics, and advanced data use cases. The position will work across IT and operational environments to support trusted data delivery for functions such as finance, supply chain, operations, commercial teams, and corporate analytics.</p><p><br></p><p>Responsibilities:</p><p>• Design, build, and maintain large-scale data pipelines that move information from enterprise and operational source systems into structured data layers for analytics and reporting.</p><p>• Develop curated and semantic data models that support business intelligence platforms, downstream applications, and data-driven decision-making across the organization.</p><p>• Connect manufacturing and operational technology data sources using approved integration methods while coordinating with plant and controls teams to protect system reliability and safety.</p><p>• Establish data quality standards through validation rules, automated testing, and monitoring processes that improve accuracy, completeness, and timeliness of delivered datasets.</p><p>• Implement observability practices such as lineage tracking, alerting, and operational runbooks to strengthen support processes and reduce production issues.</p><p>• Apply security and governance controls including access management, secrets handling, data classification, and retention practices aligned with enterprise policies.</p><p>• Automate deployment workflows with Git-based CI/CD processes to promote consistent releases across environments and improve delivery reliability.</p><p>• Tune platform performance and resource usage by optimizing processing strategies, scaling approaches, and storage patterns to balance speed and cost.</p><p>• Partner with BI, data, and IT stakeholders to define data contracts, document solutions, and provide operational knowledge transfer to internal teams and external partners.</p><p><br></p><p><br></p><p>02710-0013476075</p><p><br></p>
We are looking for a Data Engineer to 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.
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>Join a growing data engineering team supporting mission-critical analytics and business operations within the <strong>energy, commodities trading, oil & gas, or financial services sector</strong>. This role is focused on designing and supporting cloud-based data solutions using <strong>Python, Snowflake, and AWS</strong>, enabling scalable, reliable, and high-performance data platforms.</p><p>You will work closely with business stakeholders, analysts, and engineering teams to build production-grade data pipelines, modernize legacy data environments, and deliver trusted datasets that support operational and strategic decision-making.</p><p><br></p><p>Responsibilities</p><ul><li>Design, develop, and maintain scalable <strong>Python-based data pipelines</strong> that ingest, transform, and deliver data from internal and external sources.</li><li>Build and optimize data models within <strong>Snowflake</strong>, ensuring performance, scalability, and cost efficiency.</li><li>Develop ELT/ETL solutions leveraging cloud-native AWS services.</li><li>Create, monitor, and support batch and near real-time data integration workflows.</li><li>Work with structured, semi-structured, and time-series datasets from operational, trading, financial, and market data systems.</li><li>Modernize legacy data processes and migrate legacy database workloads into modern cloud architectures.</li><li>Implement data quality, reconciliation, monitoring, and alerting capabilities across the data platform.</li><li>Collaborate with analysts, traders, business users, and technology teams to deliver data solutions aligned with business objectives.</li><li>Participate in code reviews, testing, documentation, and deployment activities following engineering best practices.</li><li>Support production environments and troubleshoot data pipeline issues as needed.</li></ul><p><br></p><p><br></p><p><br></p>