Backend/Data Engineer, Coverage Intelligence

Bold Penguin is hiring a Backend/Data Engineer to build the data foundation and production services for its Coverage Intelligence team. The role owns data pipelines, services, quality, lineage, security, and reliability while partnering with AI engineers and domain specialists to integrate coverage data into the wider platform.

Responsibilities:

• Design, build and operate the pipelines and data stores behind coverage intelligence
• Build the services and data contracts that deliver coverage insights to other teams and products
• Ensure every result can be traced back to its source, with strong data quality and lineage
• Build the data infrastructure that lets the team measure accuracy and improve it with every release
• Own the reliability, performance and cost of the team’s production services
• Uphold security and privacy standards for sensitive policy and customer data
• Partner with engineers and specialists across teams to integrate coverage data into the wider platform
• Other duties and responsibilities as assigned

Requirements:

• 5+ years' experience in backend or data engineering, building and operating production services and pipelines
• Strong Python and SQL
• Experience with MongoDB and relational databases (PostgreSQL or similar)
• Experience designing APIs and data contracts consumed by other teams
• Experience with workflow orchestration (e.g., Prefect or Airflow) and batch and event-driven processing
• Hands-on AWS experience, including containers, infrastructure as code and observability tooling
• Experience modeling versioned, effective-dated reference data
• Working knowledge of CI/CD pipelines
• Excellent written and verbal communication skills
• Works autonomously with minimal direction, sets a clear path through ambiguity, and holds a high bar for quality
• Thrives on the energy of a start up: comfortable with pace, changing priorities, and building the function while running it
• Experience supporting machine learning or LLM systems in production, such as data pipelines, evaluation data or model serving (strongly preferred)
• Experience with search stores such as OpenSearch (preferred)
• Experience supporting LLM observability or evaluation tooling (preferred)
• Insurance or insurtech experience, including familiarity with insurance concepts and insurance-specific canonical data models (preferred)