Data Engineer

SafeLease Insurance Services LLC

$130K — $225K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3-6 years of experience in data infrastructure or backend systems in a production environment.
  • Strong proficiency in Python with emphasis on writing clean and testable code.
  • Advanced SQL skills including complex joins and query optimization.
  • Proven experience designing and deploying cross-system ETL/ELT data pipelines.
  • Ability to interpret and become an expert on the data you work with.
  • Strong collaborative skills to work effectively with cross-functional teams.

Responsibilities

  • Design and build end-to-end data pipelines integrating various internal and external sources.
  • Create transformations across OLTP, OLAP, and S3 infrastructures.
  • Develop backend Python services and APIs for data access.
  • Establish monitoring and alerting frameworks to proactively identify issues.
  • Make data architecture decisions that enhance agility and scalability.

Benefits

  • Work in a hybrid model, spending 3 days a week in the office in NYC or Austin.
  • Collaborative team environment with opportunity to influence data strategy.
  • Exposure to a wide range of technologies and systems.
  • Opportunity to work in a growing field, particularly in insurtech or proptech domain.
Full Job Description
This position requires working in the office 3 days per week in either New York City or Austin, TX. Applicants who are unable to work from either office location or are not willing to relocate will not be considered.

About The Role

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

What we're looking for

3-6 years working on data infrastructure or backend systems in production

Strong Python: you write clean, testable code and know when to reach for a library vs. rolling your own

Strong SQL: complex joins, window functions, CTEs, and query optimization feel natural

Experience designing and shipping cross-system data pipelines (ETL/ELT) that are reliable in the real world

Comfort interpreting data - you become the expert on the data you touch

Collaborative instincts: you'll work closely with product, frontend, analytics, research

Nice to have

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

Compensation: $130,000 to $225,000 base, depending on experience and qualifications.

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