Data Engineer

SafeLease•New York, NY

7d•$130,000 - $225,000•Hybrid

About The Position

As a Data & Backend Engineer building our Data Platform, you'll design and build our data infrastructure from the ground up: ingestion pipelines that span multiple systems, Python and SQL transformations that give the whole company a trustworthy view of our business, and backend structures making that data accessible where it's needed. You'll be a force multiplier for every team at SafeLease. What you'll build: End-to-end data pipelines integrating sources across our internal and external apps, 3P vendors and Saas systems Transformations within and between infrastructure: OLTP, OLAP and S3 Backend Python services and APIs that expose platform data to internal consumers and downstream workflows Monitoring, alerting, and data quality frameworks so we know when something breaks before anyone else does Data architecture decisions that will create agility and the ability to scale the business

Requirements

3–6 years working on data infrastructure or backend systems in production
Strong Python: clean, testable code, knowing when to use libraries vs. custom solutions
Strong SQL: experience with complex joins, window functions, CTEs, and query optimization
Experience designing and shipping cross-system data pipelines (ETL/ELT) that are reliable
Comfort interpreting data and becoming an expert on the data touched
Collaborative instincts: ability to work closely with product, frontend, analytics, and research teams

Nice To Haves

Experience with dbt for SQL-native transformation layers
Familiarity with Airflow, Prefect, or another orchestration framework
Exposure to AWS Lambda, IAM, KMS, MWAA, ECS/EKS
Background at an insurtech, proptech, or similarly regulated domain
Opinions about data modeling: star schema, OBT, normalization tradeoffs
Experience being one of the first data engineers at a company

Responsibilities

Design and build data infrastructure from the ground up
Create ingestion pipelines that span multiple systems
Develop Python and SQL transformations for a trustworthy business view
Build backend structures to make data accessible
Integrate data sources across internal and external apps, 3P vendors, and SaaS systems
Perform transformations within and between OLTP, OLAP, and S3 infrastructure
Develop backend Python services and APIs to expose platform data
Implement monitoring, alerting, and data quality frameworks
Make data architecture decisions to create agility and scalability