Top Data Engineer Jobs

Senior consulting data engineer responsible for leading complex data engineering projects, coding robust solutions, designing complex data models, troubleshooting and optimizing data operations, mentoring engineers, interfacing with customers and cross-functional teams, and ensuring quality through testing, code reviews, and performance tuning to deliver on-time, on-budget solutions.

Build and maintain data pipelines and dbt models, own reporting and dashboards across Finance, GTM, Product, and Engineering, support third-party financial data integrations, enable GTM and customer-facing analytics, and ensure data quality, testing, and documentation.

Design, build, and maintain scalable data pipelines and architectures. Perform data extraction, cleansing, transformation, and ensure data quality and accessibility. Collaborate with data scientists, analysts, and product teams to deliver data solutions and troubleshoot data issues.

Design, architect, and deliver scalable data pipelines and storage solutions using big data and cloud technologies. Lead technical strategy, mentor engineers, ensure data governance, security, and performance, and collaborate with Data Science and Product teams to support analytics and ML initiatives.

Design, build, and maintain scalable ELT pipelines and data models for insurance (Guidewire) domains and Generative AI. Ensure data quality, performance, governance, and security; support analytics, AI model training (embeddings, vector DBs), dashboards, testing, and mentoring.

Design, develop, and maintain ETL pipelines, databases, and data visualizations to support 300mm semiconductor manufacturing. Analyze operational performance, automate data extraction, troubleshoot systems, collaborate with stakeholders, and integrate emerging technologies to improve manufacturing efficiency.

Build and maintain ingestion pipelines, Python services, and dbt models on AWS and Snowflake. Own operational on-call responsibilities, migrate pipelines to Airflow, contribute to CI/CD, collaborate with BI/Analytics, and mentor junior teammates.

Design, build, and maintain scalable data pipelines, lakes, and infrastructure using Databricks, Spark, Python, and AWS. Collaborate with ML engineers, data scientists, and analysts to deliver data products, ensure data quality and governance, implement DevOps/SDLC practices, mentor junior engineers, and evaluate new data technologies.

Architect, build, and maintain Snowflake-based ELT pipelines and production data models. Implement observability, data quality, and governance; optimize cost and freshness. Partner with Analytics, Product, and Engineering, use dbt/CI-CD and AI-assisted tooling, and participate in reviews and architecture planning to support analytics, BI, and ML.

Design, build, modernize, and maintain operational and analytical data capabilities for Wealthscape Reporting, Analytics and Insights. Perform solution design, data analysis, ETL development, and production rollouts using Snowflake, AWS, cloud databases, and CI/CD pipelines. Collaborate across teams in a fast-paced financial services environment.

Design, build, and maintain operational and analytical data platform capabilities using Java Spring Batch, Python, AWS, Oracle, and Snowflake. Deliver end-to-end development, production rollout, and support; improve financial product data quality, modeling, and SQL performance; collaborate with business partners and squads.

Design, build, and maintain scalable batch and real-time data pipelines and platform components. Produce curated datasets, ensure data quality, observability, and lineage, and collaborate cross-functionally to deliver data products that support analytics, experimentation, and ML.

As a Data Engineer, you will develop data-driven decision analysis products for the DoD, ensuring effective stakeholder engagement, and leveraging advanced analytics and machine learning techniques.

The Data Engineer will develop data-driven decision analysis products, provide analytic consulting, support stakeholders with tools, and optimize defense systems for national security.

The Data Integration Lead designs and manages data ingestion pipelines, ensuring data integrity and security while supporting ETL processes in classified environments.

The Principal Data Engineer will lead development projects, design scalable data pipelines, ensure data quality, and mentor a team of engineers while collaborating with stakeholders.

Develop and implement large-scale Big Data solutions using Java, Hadoop, NoSQL, and MPP technologies. Design and optimize distributed, data-intensive systems, participate in architecture discussions, collaborate with senior architects and offshore teams, and deliver high-quality projects. Engage with clients, conduct technical sessions, create documentation and case studies, and share knowledge across the organization.

Lead Data Engineer responsible for building, optimizing, and operating secure, scalable data pipelines and platforms. Develop and run batch and streaming pipelines, workflow orchestration (Airflow), SQL-based transformations, and production-grade Python/PySpark code. Collaborate with analysts and data scientists, own system reliability and security, mentor junior engineers, and apply enterprise-authorized AI tools with strong validation and data sensitivity practices.

Design, build, test, and maintain batch and streaming data pipelines; ingest data from varied sources; write SQL and Python transformations; monitor data quality and observability; support analytics, reporting, and data science; participate in code reviews, troubleshooting, and production support; collaborate with stakeholders to deliver scalable data solutions.

Design, build, and maintain cloud-based data pipelines and data products across AWS, Azure, or GCP. Advise clients on cloud data architectures, implement production data solutions, and collaborate with users, developers, and analysts to maximize data value.

Design, build, and maintain cloud-based data pipelines and data architecture on AWS/Azure/GCP. Advise clients on cloud ingestion and processing, collaborate with stakeholders, and deliver production-ready data products using modern data tools.

Design, build, and maintain cloud data pipelines and data products across AWS, Azure, or GCP. Advise clients on cloud data architecture, implement production database and ETL/streaming solutions, collaborate with stakeholders, and evaluate architectural tradeoffs to meet business needs.

Design, build, and maintain cloud data pipelines and data architecture on AWS, Azure, or GCP. Advise clients on cloud ingestion and processing strategies, collaborate with stakeholders to maximize data value, and deliver production data products using modern databases, ETL/scripting, and engineering best practices.

Design, build, and maintain cloud data pipelines and architectures on AWS/Azure/GCP. Advise clients on cloud ingestion/processing strategies, implement production data products, collaborate with stakeholders, and evaluate architectural tradeoffs.

Design, build, and maintain cloud-based data pipelines and architectures on AWS/Azure/GCP. Advise clients on cloud data strategies, collaborate with stakeholders, implement production data products, and articulate architectural trade-offs.