Top Senior Data Engineer Jobs

Lead architecture, strategy, and hands-on execution for Faire's data platform. Build and scale secure, cost-efficient data ingestion, ETL/ELT, warehousing, orchestration, monitoring, and governance. Mentor engineers, influence cross-team priorities, and drive performance and cost optimization for analytics and data products.

Ensure timely, high-quality data conversions from legacy systems to new platforms. Work with Implementation Specialists and Project Managers to execute conversion tasks, validate data integrity, troubleshoot issues, support deployments, and assist scheduling and customer communications.

Lead design and delivery of large data products and pipelines, mentor senior engineers, set standards and best practices, promote data/analytics across business units, collaborate on governance and curated data catalog, and present technical work externally.

Architect and scale cloud data platforms and ETL/ELT pipelines (batch and near-real-time), ensure data quality and observability, implement CI/CD for data infrastructure, collaborate with stakeholders and mentor junior engineers to deliver analytics and machine-learning-ready data products.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Design, build, and own robust batch and real-time data pipelines and golden datasets using SQL and Python. Ensure data quality, performance, schema design, and SLAs while partnering across engineering, product, and business teams. Advocate tooling and best practices, document datasets, and deliver reliable analytics infrastructure at petabyte scale.

Lead design and delivery of Databricks-based Lakehouse solutions and end-to-end data engineering projects. Build and optimize ETL, streaming and batch pipelines, integrate cloud and on-prem systems, mentor team members, support pre-sales, and ensure governance, security, and platform performance.

Lead ownership of data infrastructure and ETL: design, build, and maintain Airflow pipelines ingesting from Postgres and SaaS sources; optimize Snowflake/BigQuery warehouses and dbt transformations; drive architecture, mentor teammates, and align data platform roadmap with business needs.

Lead design and implementation of scalable batch and streaming data infrastructure. Build and maintain ETL/ELT pipelines, ensure data quality and observability, troubleshoot production issues, mentor engineers, and partner with cross-functional teams to deliver reliable, self-serve data products.

Lead design and implementation of scalable data architectures and pipelines (real-time and batch), mentor junior engineers, ensure pipeline reliability and security, adopt new tools, collaborate cross-functionally, and implement data governance.

The Senior Data Engineer will design and maintain data architectures, work with operations teams, solve complex data challenges, and document decisions for stakeholders.

Lead design and implementation of scalable ETL/ELT pipelines and Snowflake data models. Optimize workflows, ensure data quality and observability, support BI (Tableau, Domo, Power BI), mentor engineers, and drive data platform architecture and roadmap.

Design, build, and operate a scalable, resilient Data Lakehouse. Lead architecture, evaluate open-source tooling, ensure performance and usability, mentor engineers, collaborate across teams, and drive DevOps and cloud best practices.

Founding technical leader for the data platform: build and operate ingestion, enrichment, batch and realtime pipelines; design storage, modeling, and governance; integrate LLM/ML workflows and vector search; hire and lead a small data team; and collaborate with engineering, product, and leadership to productionize data for valuations, analytics, and APIs.

Design and build Spark ETL pipelines on an AWS data platform, collaborate with stakeholders to deliver reliable large-scale data products, optimize and maintain data infrastructure, ensure data quality/governance, and manage platform operations and incident response.

As a Senior Data Engineer, you will design, build, and scale data pipelines and analytics capabilities, focusing on data modeling, ingestion, and automation using Python and PySpark in a healthcare context.