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Data Engineer

Work from home Full-time role Hiring

Greenlight Rent, formerly Rhino + Jetty, is making housing more affordable and accessible for millions of renters each year. We're the market-leading rental housing platform building simpler, more accessible ways for people to move into homes — and for property managers to lease with confidence. Our technology removes friction from the move-in process, lowers upfront costs for renters, and helps property managers make faster, more accurate decisions. We support a network of 3 million rental units nationwide and work with 47 of the NMHC Top 100 property owners, including Greystar, Brookfield, Asset Living, UDR, and more. We pioneered security deposit insurance and continue to push the industry forward with a growing suite of products — from deposit management to lease guarantees and loss-of-employment protection. We're growing quickly, tackling real problems at scale, and building technology that's changing how renting works. In this role, you will: 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 We’re ideally seeking: 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). Experience with Data Lakehouse architectures (Hudi, Iceberg) is a plus. 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 Benefits: Base Salary Range: $135,000 - $175,000 Rhino + Jetty has partnered with a number of compensation benchmarking tools to determine competitive and fair market pay bands for our size and stage. Our goal is to ensure each employee is paid equitably and competitively while also maintaining a consistent and standardized methodology. Individual pay decisions are based on a number of factors including qualifications for the role, experience level and balancing internal equity relative to other teammates. Base salary is just one part of our Total Rewards Package here at R + J. In connection with this position, we also offer: Competitive cash compensation package including base salary, milestone based bonus, and other financial perks Medical, Dental, and Vision coverage (up to 90% employer contribution) - eligible from your start date 401(k), HSA, Life & Disability Insurance Coverage ($0 employee contribution for additional insurances) Unlimited PTO Policy Generous Paid Parental Leave Stock option plan to give our employees a direct stake in R + J’s success Remote-first work culture with opportunities to collaborate as a team in person Monthly lifestyle stipend to fit your needs (meals, wellness, co-working)

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