> Markdown version of [/jobs/ext/3055111-sr-data-engineer](https://www.wearedevelopers.com/jobs/ext/3055111-sr-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Engineer - **Company:** eHealthinsurance Services, Inc - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $115,000.0 - $143,800.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Amazon S3, Computing Platforms, Automation of Tests, Big Data, BigQuery, Cloud Database, Code Review, Computer Programming, Continuous Integration, Information Engineering, Data Governance, Extract Transform Load (ETL), Dataspaces, Cursor (Graphical User Interface Elements), DevOps, Apache Hive, Python (Programming Language), Machine Learning, MongoDB, NoSQL, Performance Tuning, Power BI, Cloud Services, DataOps, Software Construction, Software Engineering, SQL Databases, Data Streaming, Tableau (Software), Cloud Platform System, GitHub Copilot, Informatica Powercenter, Snowflake, Apache Spark, Event Driven Architecture, Containerization, Data Lakes, Git Flow, Kubernetes, Information Technology, Cassandra, Performance Monitor, Apache Kafka, Machine Learning Operations, Data Delivery, Api Design, Restful APIs, Looker Analytics, Software Version Control, Data Pipelines, Docker, Amazon Redshift, Databricks - **Published:** September 24, 2026 - **Apply:** https://ehealthinsurance.wd5.myworkdayjobs.com/EHI/job/USA-Remote/Sr-Data-Engineer_R4383 ## About the Role * 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., * 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 frameworks (e.g., dbt, Spark, Informatica, Matillion), including framework selection and design trade-offs. * Experience with NoSQL databases (e.g., MongoDB, Cassandra, Hive). * Substantial experience with cloud platforms, preferably AWS (e.g., S3, Glue, Lambda, Redshift, EMR). * Strong command of data modeling (star/snowflake schema), data governance, and security principles, with experience setting standards for others. * Demonstrated experience mentoring engineers and/or leading technical initiatives. * Excellent communication skills, with the ability to influence cross-functional stakeholders and technical direction. Preferred: * Hands-on experience with Databricks and Delta Lake. * Deep knowledge of event-driven architectures and tools (e.g., Kafka, Kinesis). * Experience designing RESTful APIs for data delivery and ML model serving. * Experience with containerization and orchestration (Docker, Kubernetes) in production. * Visualization experience with tools like Tableau, Power BI, or Looker. * Exposure to healthcare or health tech, including EHR, claims data, or call center * analytics. * Experience operating in regulated environments (HIPAA, SOC 2, etc.). * Track record of driving automation, data observability, and proactive monitoring * initiatives. ## Description * 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., * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Database DevOps with Containers](https://www.wearedevelopers.com/videos/145-database-devops-with-containers) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)