Data Engineer

Rhino + Jetty is a rental housing technology platform making housing more affordable and accessible for renters and property managers. The Data Engineer will design and implement scalable data infrastructure, pipelines, models, and integrations, while partnering with Risk to support insurance reporting and enabling governed self-service analytics.

Responsibilities:

• Contribute to the design and implementation of scalable data infrastructure, pipelines and models for core data assets
• Drive code quality, reliability, and engineering best practices across the data stack
• Partner closely with the Risk team to build robust, automated data pipelines for insurance reporting processes, including actuarial and bordereaux reports
• Design and implement data integration solutions to consolidate siloed datasets across the organization, establishing unified data models and improving accessibility
• Build and maintain data infrastructure that enables self-service analytics capabilities while enforcing data governance, quality controls, and security standards

Requirements:

• Proven end-to-end ownership of data solutions from requirements through delivery, effectively balancing business needs with technical realities. Own the outcome
• Experience working in a fast-paced, high-growth environment with a track record of delivering reliable data solutions
• Proven expertise across the modern data stack, including cloud data warehouses (Snowflake, BigQuery), transformation frameworks (dbt), orchestration platforms (Airflow, Dagster), data integration tools (Fivetran, Airbyte), and business intelligence platforms (Tableau, Looker)
• Background in fintech or insurtech with experience building and maintaining data pipelines for financial product reporting (e.g. actuarial reports, loan tapes, regulatory filings)
• Strong software engineering fundamentals including version control, testing, CI/CD, and data quality validation
• Proven ability to collaborate with cross-functional teams (analytics, product, risk) to understand requirements and deliver scalable data solutions
• Experience with SQL, Python, and modern data engineering best practices
• Experience with Data Lakehouse architectures (Hudi, Iceberg) is a plus