Top Data Engineer Jobs

The role involves engineering modern data platforms, focusing on data ingestion, transformation, and storage while utilizing Azure services and MS Fabric, supporting an investment management firm.

The Senior Bioinformatics Data Engineer will build data pipelines, implement clinical data ingestion, and optimize platform infrastructure while ensuring data quality and compliance with legal standards.

Lead design, build, and optimize scalable ETL/ELT data pipelines and analytics platforms using Databricks and Spark. Integrate and transform source data into analytics-ready layers, maintain data documentation and lineage, optimize SQL Server performance, collaborate with product and engineering teams, and apply AI-enabled tools responsibly to drive business insights.

Designs, builds, and maintains scalable ETL pipelines and databases; integrates large-scale data for analytics; develops and tests code, queries, and reports; ensures data quality and governance; leads solution development, trains users, and supports ML and BI initiatives.

Design and maintain executive Power BI dashboards and Power Apps, translate clinical and financial data into actionable insights, build frontend data products, educate end-users, partner with backend engineers to build pipelines in Microsoft Fabric, and perform ad-hoc healthcare analytics and modeling to support operational leaders.

Provide senior-level data engineering for analytics: resolve complex technical issues, build decision-support reports and dashboards, lead projects, prepare and integrate data, coach staff, and ensure high-quality analytics to support academic, research, and healthcare goals.

Design, build, and maintain scalable cloud data pipelines and Databricks-based data platforms. Manage Databricks clusters and Delta Lake tables, integrate with Azure services, implement CI/CD and monitoring, define data warehouse architecture and governance, collaborate with stakeholders, and support advanced analytics and future AI/ML use cases.

Design, build, and maintain data pipelines, ETL processes, and data warehousing solutions using Python and GCP/BigQuery. Ensure data quality, optimize storage and processing, support new data products, and mentor junior engineers while collaborating with the CTO and team.

Design, develop, and maintain scalable data pipelines, ETL processes, and BigQuery/GCP-based data storage. Ensure data quality, implement monitoring, assist product launches, mentor junior engineers, and collaborate closely with the CTO and team.

Design, build, operationalize, and maintain enterprise-scale data pipelines and platforms. Develop ETL/ELT workflows, parse structured and unstructured data, troubleshoot Palantir Foundry pipelines, and lead cross-functional teams to support analytics, monitoring, and scalable data solutions for mission-driven projects.

Build scalable, secure data pipelines and ETL/ELT processes in cloud environments to standardize and integrate data, create data models/marts, support data science, automate workflows, and improve data accessibility across the enterprise.

Design, implement, and maintain scalable data pipelines and storage for intelligence operations. Build ETL and real-time ingestion, optimize queries and data models, enforce data quality, governance, and security per IC standards, and collaborate with analysts and mission partners.

Build, optimize, and maintain ETL/ELT data pipelines and cloud-based data environments (AWS/Azure). Support relational databases and data warehouses, ensure data quality and automation, troubleshoot integration issues, and enable analytics for aviation and readiness initiatives.

Design, build, and support scalable data warehouse solutions and pipelines.Implement data models, source-to-target mappings, DDL, and SCDs; support governance, metadata management, migration/modernization, troubleshooting, and cross-functional delivery.

Design, build, and maintain large-scale GCP data pipelines and data warehouse solutions using Dataproc, GCS, BigQuery, Hadoop/Spark/Hive and Airflow. Mentor engineers, run agile ceremonies, prioritize backlog, provide on-call support, and deliver data models and products at multi-TB/PB scale.

Design and develop AWS-based data platforms, build and maintain ETL pipelines using PySpark, perform data modeling and governance, integrate event-driven systems with Kafka, manage containerized deployments with Docker and Kubernetes, and produce clear documentation while collaborating with stakeholders.

Design, develop, and maintain scalable ETL pipelines using Ab Initio to transform upstream data for Oracle Financials SaaS. Perform data profiling, quality assessments, complex SQL development, Unix/Linux scripting, metadata management in EME, deployment support, performance tuning, and collaborate with architects and analysts. Provide operational support and mentor junior analysts while ensuring compliance and risk controls.

Lead Data Engineer responsible for building technical solutions, collaborating with Agile teams, utilizing big data technologies, and developing cloud-based data warehousing solutions to enhance user experiences.

The Lead Data Engineer will design, develop, and implement technical solutions while collaborating with Agile teams and leveraging data technologies to solve business problems.

Lead design, build, test, and support cloud-based data solutions and streaming pipelines. Collaborate with Agile teams, mentor engineers, perform code reviews and unit tests, and leverage big data, data warehousing, and cloud technologies to deliver scalable payment-network capabilities.

Design, build, test, and support cloud-based data solutions and pipelines. Collaborate with Agile teams and product managers to deliver distributed, real-time, and batch systems using big data, NoSQL, and cloud data warehousing technologies. Mentor engineers and participate in code reviews and performance tuning.

As a Data Engineer, you will design and implement data pipelines, analyze requirements, and develop software solutions to drive operational efficiency.

The Azure Data Engineer will design and develop ETL processes, utilizing Python and Azure Synapse Analytics, to manage data integration and ensure data accuracy. Responsibilities include performance tuning, data modeling, and collaboration across teams.

Lead architecture and delivery of scalable data infrastructure: design and optimize ETL/ELT pipelines, enterprise data models, and data quality frameworks. Define platform standards, mentor engineers, drive cross-functional initiatives, and partner with analytics, data science, and engineering stakeholders to ensure reliable, production-grade data assets.

Design, build, and maintain scalable data pipelines and platform infrastructure. Define data governance, monitoring, and quality standards. Partner cross-functionally with Product, Engineering, Analytics, and Data Science. Drive technical decisions, performance optimization, and infrastructure-as-code for a growing data platform supporting patients, providers, and business teams.