eHealth, Inc.

Data Engineer

• Serve as a subject-matter expert on the data ecosystem, including internal systems and third-party data sources
• Guide architectural decisions across teams
• Architect, build, and maintain scalable data pipelines and real-time streaming architectures using frameworks such as Spark, Kafka, and dbt
• Design and drive adoption of workflow automation and orchestration standards using Apache Airflow or Matillion
• Lead technical design for production-grade ML pipelines and APIs serving model predictions
• Leverage AI-assisted development tools such as GitHub Copilot, Claude Code, and Cursor for pipeline development, code review, and testing
• Establish team norms for effective and responsible use of AI-assisted development tools
• Own data quality, observability, lineage, and governance strategy
• Define monitoring, alerting, and metadata tracking best practices
• Drive logical and physical data modeling efforts and schema design decisions
• Partner with DevOps and infrastructure teams on platform architecture, performance optimization, and security/compliance strategy
• Mentor junior and mid-level data engineers through code review, technical guidance, and knowledge-sharing
• Evaluate emerging data tools and technologies
• Make build-vs-buy and adoption recommendations to engineering leadership
• Demonstrate eHealth's values in behaviors, practices, and decisions

Senior Data Engineer