Top Data Engineer Jobs

The Data Engineer is responsible for developing data infrastructure, building data pipelines, managing data quality, and integrating analytics tools to support design and project operations.

The ETL Lead will design and manage scalable data pipelines, optimize data lake architectures, and lead data engineering initiatives in a cloud environment.

As a Data Engineer, you will design and implement data solutions, automate processes, and support data analytics for the Department of Defense.

The Data Engineer will develop scalable data pipelines, build applications using Palantir Foundry, and collaborate with stakeholders on data integration for decision-making.

As a Data Engineer Lead, you will develop and maintain complex data applications, oversee data engineering activities, mentor teams, and work on mission-driven projects involving data insights.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts; integrate data for analytics and Data Science; optimize Hadoop/HDFS and queries; implement CI/CD and cloud-based big-data solutions; collaborate with Data Science to operationalize models and troubleshoot systems.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts. Integrate data from multiple sources, ensure data quality, optimize Hadoop/HDFS workflows, collaborate with Data Science to operationalize models, and recommend tooling and system improvements.

Design, build, and maintain large-scale data structures, ETL pipelines, and data models to support analytics and reporting. Integrate data from varied sources, collaborate with Data Science to operationalize models, optimize Hadoop/Spark workflows, and ensure data quality and accessibility for internal customers.

Design, build, and manage large-scale data structures, pipelines and ETL workflows. Develop real-time and batch analytic systems, integrate diverse data sources, ensure data quality and accessibility, and collaborate with Data Science to operationalize models using Hadoop, GCP, Python, Spark, Airflow, and related tools.

Design, build and maintain large-scale data structures, ETL pipelines, and data marts. Integrate data sources, ensure data quality, support analytics and Data Science teams, and optimize Hadoop/cloud-based processing using tools like Spark, Airflow, and Kafka.

Build and maintain large-scale data structures, pipelines, and ETL workflows; design data architectures and models; integrate data for analytics and data science; collaborate with Data Science to productionize models; ensure data quality, accessibility, and compliance for healthcare and retail use cases.

Build and maintain large-scale data structures, pipelines, and ETL workflows; design databases and data marts; collaborate with Data Science to integrate models; ensure data quality and accessibility; leverage Hadoop, Spark, Python/Java, and cloud platforms to deploy scalable ML-enabled data solutions.

Design, build, and maintain large-scale data structures, ETL pipelines, and data architectures to support analytics and reporting. Integrate data sources, ensure data quality and accessibility, collaborate with Data Science to operationalize models, and troubleshoot/optimize systems using Hadoop, cloud platforms, and modern data tooling.

Design, build, and maintain large-scale data structures, ETL pipelines, and data models on cloud platforms (GCP/BigQuery, AWS, Azure). Collaborate with Data Science to integrate models, ensure data quality, troubleshoot systems, and support analytics modernization.

Build and manage large-scale data structures, ETL pipelines, and data marts; design database systems and distributed computing architectures; integrate data for analytics and productionize ML/NLP models; collaborate with Data Science, ensure data quality, optimize queries, and troubleshoot systems.

Design, build, and maintain cloud-native data platforms and large-scale ETL pipelines. Integrate data for analytics and data science, support CI/CD and production operations, advise on tooling, ensure data quality and privacy, and mentor junior cloud engineers to support healthcare data modernization.

Build and maintain large-scale data structures, ETL pipelines, and data models to support analytics and reporting. Use Google Cloud services (BigQuery, Cloud SQL, Cloud Storage) and programming in Python/Java/R to integrate, standardize, and ensure data quality. Collaborate with Data Science to operationalize models, optimize queries, troubleshoot systems, and recommend tooling for analytics modernization and platform capabilities.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts to support analytics and Data Science. Collaborate with Data Science to integrate models, ensure data quality and accessibility, optimize cloud queries (GCP/AWS), troubleshoot systems, and recommend tooling and solutions to meet business requirements.

Design and build large-scale data architectures, ETL pipelines, and data marts on cloud or on-prem platforms. Integrate and operationalize models, ensure data quality and governance, and support analytics and reporting for internal stakeholders.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts to support analytics. Develop database systems, integrate models with automated processes, optimize Hadoop/HDFS queries, ensure data quality, troubleshoot systems, collaborate with Data Science, and evaluate tooling. Work includes cloud platform integration (Azure/AWS/GCP) and software development for enterprise/web applications.

Develop and maintain large-scale data structures, ETL pipelines, and data models; integrate data science models into automated workflows; optimize Hadoop/Spark processing; ensure data quality and accessibility; collaborate with stakeholders to support analytics and reporting.

Design, build, and manage large-scale data structures, pipelines, and ETL workflows. Develop real-time and batch processing, integrate data for analytics and ML, collaborate with Data Science to productionize models, ensure data quality and accessibility, and recommend tools and architectures for scalable data solutions.

Design, build, and maintain large-scale data structures, ETL pipelines, and data models; integrate ML models with production workflows; ensure data quality and accessibility; optimize queries and troubleshoot systems to support analytics and reporting.

Design and develop scalable data solutions and ETL pipelines ingesting healthcare and retail data; build predictive models and statistical analyses; support deployment of insights across channels; collaborate on backend services, DevOps, and cloud cluster management to solve complex business problems.

Design, build, and maintain large-scale data structures, ETL pipelines, and data architectures for real-time and batch analytics. Collaborate with Data Science to integrate models, ensure data quality, optimize queries, and deploy ML systems in cloud environments. Troubleshoot, test, and recommend tools to meet business reporting and analytic needs.