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Reserv is an insurtech company founded by insurance veterans and backed by Bain Capital and Altai Ventures. The company is building AI and automation technology to modernize claims processing, automating manual tasks for TPAs, insurance technology providers, and adjusters.
As a Data Engineer, you will design, build, and maintain production data pipelines that ingest data from applications, APIs, databases, and external partners. You'll develop data models that make claims and operational data accessible, consistent, and useful for analytics and downstream applications. Your responsibilities include building automated tests, monitoring, and alerts to catch data quality issues early; partnering with business and technical teams to define requirements and deliver trusted datasets; and improving pipeline and query performance while managing infrastructure costs.
You will own production workflows including troubleshooting, backfills, and recovery from upstream changes. You'll apply sound engineering practices through version control, code review, automated testing, and CI/CD. Documentation of data sources, transformations, and dependencies is critical, as is protecting sensitive information through appropriate access controls.
The role is fully remote but candidates must reside in an eligible U.S. state (excluding California, Alaska, Hawaii, and U.S. territories) throughout employment.
QUALIFICATIONS:
- 6+ years of experience designing, building, and maintaining production data pipelines and platforms, with demonstrated ownership of architecture, reliability, and technical decisions
- Strong SQL and Python skills, including experience writing readable, tested, and maintainable code
- Experience with a cloud data warehouse such as Snowflake, BigQuery, or Redshift
- Solid understanding of data modeling, including dimensional models, incremental processing, and changing source data
- Experience with transformation and orchestration tools such as dbt, Airflow, Dagster, or comparable technologies
- Track record of improving data reliability through testing, monitoring, and thoughtful system design
- Comfort working with APIs, relational databases, and structured or semi-structured data
- Strong communication skills and ability to explain technical tradeoffs to colleagues with different backgrounds
- Practical approach to problem-solving, willingness to learn, and comfort taking ownership as priorities evolve
- Experience with insurance or claims data, sensitive information, or event-driven systems is a plus
