Top Data Engineer Jobs

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts to support analytics and reporting. Optimize Hadoop/Spark-based workflows, integrate cloud sources, ensure data quality, and collaborate with Data Science to operationalize models. Provide production support, monitoring, and tooling recommendations.

Build and maintain large-scale data structures, pipelines, and ETL workflows; design databases and data marts; integrate data science models into automated processes; optimize Hadoop/Spark-based systems; develop real-time and offline analytic tooling; ensure data quality and accessibility; troubleshoot, test, and recommend tools to meet analytics and reporting needs.

Design, build, and maintain large-scale data structures, pipelines, and ETL workflows. Integrate data from multiple sources, ensure data quality, support Data Science by building data marts/models, optimize Hadoop/HDFS queries, and collaborate on backend development and deployment.

Design, build, and maintain large-scale data structures, pipelines, and ETL workflows. Integrate data sources, support data marts and models, collaborate with Data Science to operationalize models, optimize Hadoop/Hive queries, and ensure data quality and accessibility.

Design, build, and optimize scalable data platforms, pipelines, and data lakes. Develop distributed data processing pipelines, automate workflows, integrate diverse data sources, implement data modeling and database design, ensure data security and governance, troubleshoot production issues, own full SDLC delivery, drive performance and reliability improvements, collaborate across teams, and mentor other engineers.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

The Data Engineer will structure and deliver translation memory data using a Translation Management System, requiring expertise in data science and cloud services.

The Data Engineer will construct data infrastructure, develop machine learning workflows, maintain data pipelines, integrate software components, and collaborate across teams to enable data-driven decisions.

Seeking an expert Data Engineer to construct data analytical infrastructure and pipelines, collaborating with Data Scientists to enhance machine learning workloads and automate data processes for national security missions.

The Data Engineer will design and maintain data pipelines on Azure, manage ClickHouse for analytics, and ensure healthcare compliance while supporting ML integration.

Lead the design and migration of a data platform architecture. Manage data pipelines, mentor teams, and ensure platform reliability.

As an FP&A Data Engineer, you will manage data pipelines, develop financial models, and automate reporting to assist management and teams in making data-driven decisions.

The Data Engineer will build and maintain scalable data pipelines, ensure data quality, and support a metadata-driven framework while collaborating with stakeholders.

Join Equifax's Global Keying & Linking team to build and maintain data pipelines, perform intermediate data quality checks, investigate stakeholder queries, analyze root causes, and drive improvements in data onboarding and feature design. Collaborate with global stakeholders, apply cloud and coding skills (Python/SQL), and support regulatory and data standards compliance while contributing to data quality assessments and operational innovations.

Design, develop, and maintain scalable data pipelines and stores to process structured and unstructured data. Build ETL/ELT workflows, scripting for data conversion, and collaborate with analysts, engineers, and data consumers to deploy and operate data platforms supporting analytics and mission-driven use cases.

Build and deploy data extraction, transformation, and loading processes and BI integrations between client systems and EAB platforms. Manage implementation projects, communicate with stakeholders, recommend integration approaches, remove delivery barriers, and foster strong client relationships to ensure timely, high-quality data integrations.

Develop and maintain manufacturing data pipelines, clean and validate production data, build dashboards and analytics (OEE, downtime, throughput), translate insights for operations, support deployment and continuous improvement, and partner cross-functionally to improve line performance and capacity planning.

Designs and implements scalable cloud-based data pipelines and architectures, defines technical scope with stakeholders, monitors production reliability, mentors junior engineers, collaborates with data scientists and analysts, and creates reusable best practices and assets to deliver trusted data for decision-making.

Maintain and monitor data pipelines that aggregate healthcare claims for the Cost Roll process. Validate and reconcile claim and provider demographic data, troubleshoot data issues, perform data quality checks, and collaborate with stakeholders to ensure reliable downstream financial and clinical systems.

Hands-on technical lead for global Azure-based data analytics environments. Own escalation support for complex incidents, performance/scalability troubleshooting on large datasets and pipelines, guide support analysts, and partner with engineering to drive durable fixes across Databricks, SQL Server/DWH, and Azure data services.

Set up test, preproduction and developer environments on physical servers; act as SQL Server DBA including security auditing; develop Big Data solutions and programs; perform user acceptance and integration testing. Requires experience with DTS/SSIS/SSRS, T-SQL, C#, PowerShell, Hive/Hadoop, and Microsoft SQL Server 2000 certification.

Lead Data Engineer responsible for designing data models, implementing data solutions, managing data pipelines, and collaborating with teams to drive technical initiatives.

Design, build, and maintain scalable data systems and pipelines (batch and streaming); perform complex data modeling and transformations; implement data architectures, governance, and automated deployment pipelines; collaborate with analytics and stakeholder teams to deliver robust, production-ready data products supporting trading and agricultural analytics.

Design, build, and maintain scalable data pipelines and data warehouse solutions on Azure. Perform source data analysis, profiling, ETL development with PySpark, support migrations from on-prem to cloud, troubleshoot production issues, collaborate in Agile teams, and contribute to ML/Generative AI initiatives and Power Apps development.