Develop the Policy Journal: Be a primary builder of our master data solution that unifies policy, commission, and accounting data.
Ensure Data Quality and Reliability: Implement robust data quality checks and monitoring.
Build the Foundational Analytics Platform: Implement and enhance our new analytics framework.
Modernize Core ETL Processes: Refactor existing Java & SQL (PostgreSQL) based ETL system.
Implement Data Quality Frameworks: Build and execute automated data validation frameworks.
Collaborate and Contribute to Design: Partner with product managers and stakeholders to understand requirements.

Requirements

5+ years of experience in data engineering
Expert-level proficiency in Python and SQL
Strong experience with modern data stack technologies, including a cloud data warehouse (Snowflake or Redshift)
A workflow orchestrator (Airflow is highly preferred)
Hands-on experience with AWS data services (e.g., S3, Glue, Lambda, RDS)
Experience in the insurance technology (insurtech) industry
Familiarity with insurance data concepts (e.g., policies, commissions, claims)
Demonstrated ability to contribute to the design and implementation of robust data models (e.g., dimensional modeling) for analytics and reporting
Ability to read and understand existing Java/Hibernate logic is a strong plus.
Excellent communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders.

Benefits

Possible Equity 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonSQLJavaETLdimensional modelingdata validationdata quality checksanalytics frameworkdata modeling

Soft Skills

communicationcollaborationdesign contribution