Senior Data Engineer

Data Engineer at Sigmoidal

Before people who manage billions of dollars open a report, someone has decided how its data is modelled, where each figure came from and who may see it. At Sigmoidal, that someone is a Data Engineer.

We build AI systems that run every day inside leading US private equity firms and fintechs, supporting the management of more than USD 200 billion in assets. Here data is the foundation of investment decisions, not just pipelines. The team is small and senior-only, so one Data Engineer shapes how the data platform is built, and answers for it.

What a Data Engineer owns, end-to-end

The data platform investment teams use for reports and decisions:

• Data modelling first, before any tool.

• Production-ready ETL/ELT pipelines on Snowflake, dbt and Airflow, in Python and SQL, for data from many sources.

• Data quality, consistency, performance and cost, down to the Snowflake bill.

• Data governance: lineage, metadata and quality checks, with tools like Atlan or Monte Carlo.

• Access control for confidential deal data. Who may see which deal is part of the data model.

• Data that business, analytics and engineering teams can use without asking you first.

Ten years forward deployed

Sigmoidal started in 2016 as one of the first AI companies in Poland, before it was fashionable and long before the OpenAI era.

Palantir calls the role "forward deployed engineer". In 2026 OpenAI and Anthropic launched companies built on the same model. We have always worked this way. For a Data Engineer it means:

• The same engineer talks to our partners, writes the code and owns the data platform in production.

• A seat at the table with the investment teams who use your data.

• No proofs of concept. Data work counts only when people use it every day and it delivers measurable value: hours saved, better decisions, lower risk.

• Colleagues from McKinsey, Google, Kraken and JPMorgan. Half of our engineers have 7+ years of experience.

You might be a fit if

• You are a senior Data Engineer, usually 5+ years, who has built cloud data pipelines and used dbt in a team.

• Your data modelling holds up when another senior engineer asks why.

• You judge your work by the business result.

• English for daily calls with the US, communicative Polish inside Sigmo.

• A plus: financial or investment data, or a background in finance or consulting.

Recruitment steps

1. Call with our recruiter.

2. Technical interview with a senior engineer from our team. No live coding, but expect hard questions.

3. Tech & business call with the team.

We respect your time: you hear back within 5 working days.