Senior Data Engineer

Senior Data Engineer

Join our AI Data Products Scrum Team as a Senior Data Engineer, supporting a Fortune 50 healthcare insurance organization in a fully remote capacity. In this hands-on role, you will be instrumental in building, optimizing, and operationalizing scalable data pipelines and reusable data assets that power advanced analytics, machine learning, and generative AI initiatives. You will work within a modern distributed data environment, collaborating with cross-functional teams to deliver reliable, production-ready healthcare data solutions. This is an opportunity to make a significant impact in a dynamic, innovative environment while enjoying comprehensive benefits and competitive compensation.

Remote Role

Contract to Hire

Compensation: $80 - $90/hour, DOE

Design, build, and maintain scalable batch and streaming data pipelines using modern distributed data technologies

Develop production data solutions using SQL, Python, and PySpark, selecting the appropriate tool for each workload

Troubleshoot, optimize, and enhance existing data pipelines to meet new data requirements and improve performance

Create reusable ingestion, transformation, reconciliation, and data-product patterns for analytics and AI use cases

Implement data-quality checks, monitoring, lineage, documentation, and provide reliable operational support for production pipelines

Utilize Git and CI/CD practices to test, review, version, deploy, and promote data-engineering assets across environments

Collaborate with lead engineers, application teams, data scientists, and platform teams on production healthcare solutions, market expansion, and AI-assisted workflows

Support AI-enabling data assets such as feature tables, vector indices, embeddings, or semantic context

Ensure compliance with data governance, cataloging, lineage, and discoverability practices, especially in regulated environments

Senior-level, hands-on experience designing, building, and supporting production data pipelines in a modern distributed data environment

Strong production experience with Databricks Data Engineering, Spark distributed computing, or the Hadoop framework

Strong SQL skills and practical experience using Python and/or PySpark for production data-engineering work

Hands-on experience with DevOps, CI/CD pipelines, and Git-based source-control workflows

Experience with ETL/ELT, batch and/or streaming processing, production debugging, performance tuning, and data-quality validation

Familiarity with columnar formats such as Parquet and Delta, plus data warehousing and data-analysis concepts

Linux scripting experience (preferred)

Exposure to data governance, cataloging, lineage, and discoverability practices (preferred)

Experience supporting AI-enabling data assets such as feature tables, vector indices, embeddings, or semantic context (preferred)

Experience working in a regulated enterprise environment, preferably healthcare or financial services (preferred)

401(k) matching plan

Medical, dental, and vision plans

Paid company holidays

Regular engagement check-ins and consultant support

Competitive hourly rates

Opportunity to work in a dynamic, innovative environment