Senior Data Engineer
We all depend on healthcare throughout our lifetimes, for ourselves, and our families and friends, but it is notoriously difficult to navigate and understand. As an industry that comprises 20% of the US economy we think healthcare should work better for all of us. At Collective Health we believe it’s time for a new day in healthcare where as members we are informed and empowered to make the right care choices when the decisions are urgent and critical.
We deliver a connected healthcare experience for over a quarter million members and 60+ companies across the nation who want the best for their employees. We've got a ton of interesting problems to solve around data pipeline design and implementation, data architecture and modeling, distributed systems, and more. If you're passionate about tackling hard problems while making a real difference in the world, we'd love to talk!
While we are embracing a remote-flexible work week, employees are expected to be within commuting distance of an office. The frequency of in-office days will be determined on a team-by-team basis closer to the reopening of our offices.
What you'll do:
- Data Pipelines - Create new pipelines and improve/maintain existing pipelines using Spark (Scala, Pyspark, Spark SQL)
- Data Modeling - Partner with analytic consumers to design logical and physical schemas, improve existing data models and build new ones
- Cross-functional Collaboration - Interface with Product, Engineering, Data Science, Analytics/BI, and Operations to understand their data needs, providing both consultative and data engineering solutions for consumers
- Build data expertise and own data quality across various business domains including healthcare claims and member experience
You will be successful in this role if you have:
- BS degree in Computer Science or related technical field, or equivalent practical experience
- 6+ years proven work experience as a data engineering, working with at least one programming language (e.g. Scala, Python/PySpark) plus SQL expertise
- 6+ years experience with schema design, dimensional data modeling, and large-scale data warehousing architecture
- Expertise in building data pipelines through efficient ETL design, implementation and maintenance
- Background working with distributed data systems such as Spark, Presto, Hive, and Redshift; Experience with schedulers/workflow management tools (e.g. Airflow) a plus
- Excellent communication skills to collaborate with stakeholders in Engineering, Product, Data Science, Analytics/BI, and Operations
Founded in 2013, Collective Health has created an ecosystem of innovative partners across care and benefits delivery, as well as built a powerful and flexible infrastructure to better enable employees and their families to understand, navigate, and pay for healthcare. By reducing the administrative lift of delivering health benefits, providing an intuitive member experience, and improving health outcomes, the company guides employees toward healthier lives and companies toward healthier bottom lines. Collective Health is headquartered in San Mateo, CA with locations in Chicago, IL, and Lehi, UT. For more information, please visit collectivehealth.com.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Collective Health is committed to providing support to candidates who require reasonable accommodation during the interview process. If you need assistance, please contact [email protected].