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StoicLane · 6 hours ago

Data Platform Engineer

Greater Chicago Area

Full-time

Hybrid

Mid, Senior Level

$120K/yr - $160K/yr

4+ years exp

StoicLane is a long-term growth platform focused on strategic investments in the Finance, Insurance & Real Estate sectors. The Data Platform Engineer will build foundational tooling and infrastructure for data-driven decisions across portfolio companies, focusing on Python development and API integrations.

Financial ServicesReal EstateReal Estate Investment

Responsibilities

Build Python SDKs and API clients from scratch for extracting data from complex source systems (Microsoft Graph, various HRISs, ERPs, custom enterprise applications)

Debug and extend open-source tools like DLT, Prefect, and DBT when standard functionality doesn't meet our needs by reading source code, filing issues, contributing patches

Design and implement reusable Python libraries and frameworks that abstract complexity and accelerate deployments across portfolio companies

Build and maintain production data pipelines, but with a focus on the engineering quality of the pipeline code itself

Work with Snowflake for data modeling, understanding how to optimize for both query performance and pipeline maintainability

Implement comprehensive testing strategies, including unit tests, integration tests, and contract tests because we ship code that runs in production across multiple companies

Collaborate directly with stakeholders at portfolio companies to translate business requirements into well-architected technical solutions

Set standards for code quality, documentation, and engineering practices across the data platform

Qualification

PythonAPIsSnowflakeAWSSQLGitDBTPrefectTesting frameworksContainerizationCI/CDOpen-source contribution

Required

4+ years writing production Python. You're comfortable with the language, the ecosystem, and modern Python development practices

Strong software engineering fundamentals: You understand design patterns, write testable code with proper separation of concerns, and think about abstractions that actually reduce complexity

You write Python from first principles, not by prompting an LLM and hoping. You use AI tools as a knowledge base and accelerant, but you could debug a stack trace or implement a complex algorithm without them

Deep understanding of APIs: REST, pagination patterns, rate limiting, authentication flows, error handling, retries with exponential backoff. You've built robust API clients that handle edge cases

Experience with Python testing frameworks (pytest) and writing tests that actually catch bugs

Solid SQL fundamentals and experience with Snowflake or other modern cloud data warehouses

Hands-on experience with AWS services (Lambda, ECS, S3, RDS) and understanding how to architect for the cloud

Git proficiency: branching strategies, pull requests, rebasing, resolving conflicts

Experience with Prefect (or Airflow/Dagster) at a level where you've dug into how it actually works under the hood

Experience with DBT or SQL where you've gone beyond writing select statements

Familiarity with DLT or similar ingestion frameworks is a plus, but we can teach this if you have the fundamentals