Data Platform Engineer

Stoic Lane is a long‑term growth platform making controlling and strategic minority investments in the Finance, Insurance & Real Estate (“FIRE”) verticals. The firm works closely with its portfolio companies by harnessing the power of data and technology to bring better service and quality to consumers. Stoic Lane Principals have contributed to creating over $4B of equity value for investors since 2004 in various entrepreneurial ventures and private investments.

Stoic Lane is raising more than $1 billion of permanent capital to invest and completed its first transaction in March 2021. A successful candidate will have an opportunity to join a small, entrepreneurial team and help shape and grow the vision of the firm.

The position is hybrid (4 days in office, 1 remote) and based in Chicago, IL.

Our Data & AI team operates as an internal consultancy for Stoic Lane and its Portfolio companies as we build the infrastructure, pipelines, and tooling that power data‑driven decisions across a diverse portfolio spanning finance, mortgage appraisal, professional services, and more.

We move fast, and we solve real problems. No committee paralysis. Just smart people building things that matter.

You’ll work alongside a small but growing team of data engineers and analysts. We value clear thinking, understanding the problem before writing code, and creating systems that others can maintain. We’re building something that scales technically and operationally, and we need engineers who care about how things are built, not just that they work. If you’re the type of engineer who reads source code when documentation is lacking, who gets satisfaction from designing an elegant abstraction, and who wants to build foundational tooling rather than just use it—we should talk.

We’re looking for a Data Platform Engineer who is first and foremost an excellent Python engineer. You’ll join our centralized Data Team and work across multiple portfolio companies, building the foundational tooling and infrastructure that powers our data platform.

This isn’t a typical "data engineer writes SQL transformations" role. You’ll be building custom SDK wrappers around vendor APIs, debugging the internals of DLT and Prefect when things break in unexpected ways, extending DBT with custom materializations, and designing reusable Python libraries that get deployed across our portfolio.

One week you might be reverse engineering an undocumented SaaS API to build a robust extraction client. The next you’re diving into Prefect’s task execution model to understand why a deployment is behaving unexpectedly. Then you’re designing a framework that lets us spin up new data pipelines with 90% less boilerplate.

We’ve invested heavily in building reproducible, templatized infrastructure. You’ll help us extend these patterns while getting exposure to problems most engineers only see once in their career.

• 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

• 4+ years writing production Python. You’re comfortable with the language, the ecosystem, and…