Sr. Data Engineer

Join us in creating a better way!At eHealth, our mission is to expertly guide consumers through their health insurance and related options when, where, and how they prefer. We’re creating a better way – one that’s transparent and trustworthy for both our consumers externally and our employees internally. Move your career forward while connecting countless people to the life- changing, quality care they deserve. Our diverse team of innovators supports one another in solving some of the toughest challenges. We’re always on the lookout for creative opportunities to do right by our customers, and each other. Together, we’re creating a better way to work, united by our common passion to make a difference.At eHealth, we're working to make health insurance more accessible, affordable, and easier to navigate for Americans nationwide. We're looking for an experienced, motivated Senior Data Engineer to join our data team. You'll take a lead role in designing scalable, high-performance data pipelines, architecting data solutions, and driving analytics and machine learning initiatives across the business. You'll partner closely with data scientists, software engineers, and business stakeholders and mentor other engineers to ensure our data is reliable, accessible, and actionable, powering mission-critical decisions in a fast-paced, regulated industry. Key Responsibilities Serve as a subject-matter expert on our data ecosystem, including internal systems and third-party data sources, and guide architectural decisions across teams. Architect, build, and maintain scalable data pipelines and real-time streaming architectures using modern frameworks (e.g., Spark, Kafka, dbt). Design and drive adoption of workflow automation and orchestration standards using tools such as Apache Airflow or Matillion. Lead technical design for production-grade ML pipelines in partnership with data scientists and ML engineers, including APIs that serve model predictions. Leverage AI-assisted development tools (e.g., GitHub Copilot, Claude Code, Cursor) to accelerate pipeline development, code review, and testing, and help establish team norms for effective, responsible use. Own data quality, observability, lineage, and governance strategy - defining monitoring, alerting, and metadata tracking best practices for the broader team. Drive logical and physical data modeling efforts in close partnership with data architects, including schema design decisions with long-term scalability in mind. 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, and make build-vs-buy and adoption recommendations to engineering leadership. Demonstrate eHealth's values in your behaviors, practices, and decisions. Specialized Skills & Competencies Advanced expertise designing scalable data pipelines, ETL/ELT workflows, data models, and real-time streaming solutions using modern data engineering frameworks and cloud-native platforms. Strong proficiency in SQL and Python or Scala, with demonstrated knowledge of software engineering practices including CI/CD, version control, automated testing, code review, and API development. Strong understanding of cloud-based data ecosystems, data quality, observability, lineage, security, and governance principles, with the ability to establish and promote scalable engineering standards and best practices. Ability to analyze complex or ambiguous technical and business problems, evaluate design trade-offs and emerging technologies, and develop practical, scalable solutions with long-term business and technical needs in mind. Strong interpersonal and communication skills with the ability to translate complex technical concepts for technical and non-technical audiences, build effective cross-functional partnerships, and influence technical decisions across teams. Demonstrated ability to lead technical initiatives, provide thoughtful technical guidance and code review, mentor engineers, share knowledge, and help elevate engineering practices and capabilities across the team. Required and Preferred QualificationsRequired: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. 5+ years of related data engineering experience with a Bachelor's degree; 3+ years with a Master's degree; or an equivalent combination of education and relevant experience. Expert-level SQL for complex query development, optimization, and performance tuning across large datasets. Strong programming skills in Python or Scala, with deep experience in software engineering best practices (CI/CD, git workflows, testing, code review). Proven experience architecting solutions on a cloud-native data platform such as Snowflake, BigQuery, Redshift, or Databricks. Deep working knowledge of modern ETL/ELT framew