Hi there! If you’re seeking a high-impact role within an ambitious and fast-growing software house, you might have just found your perfect match!

We are seeking a highly skilled and experienced Senior Data Engineer to join our team. You will be working with one of the biggest consumer insights providers in the U.S.

In this role, you will build and optimise a data evaluation pipeline in Snowflake for a financial data analytics project. The goal is to independently assess the quality and added value of new credit card transaction datasets by comparing company revenue estimates against reported financial results, while ensuring the process is scalable, cost-efficient, and automated.

You will take ownership of the pipeline end to end, from data processing and ground truth collection to quality validation and ongoing dataset evaluations.

Working hours: Availability between 5:00 PM and 10:00 PM CET is essential during onboarding; afterwards, standard hours end between 5 and 7 PM CET (depending on the day).

Ability to work partially within the U.S. time zone (during onboarding: calls up to 10:00 PM CET a few times a week; later: occasionally up to 7 PM CET)

3+ years of experience in Data Engineering, with Snowflake as a primary data platform.
Proven hands-on experience optimising Snowflake warehouses and storage for performance and cost efficiency in production environments.
Experience building and optimising pipelines processing very large datasets, including full transaction-level histories rather than samples.
SQL and Python skills, with the ability to own data pipelines end to end.

Nice to have:

Experience working with financial, market, transaction-level, or time-series data.
Familiarity with accuracy and tracking metrics such as correlation and mean absolute error (MAE).
Experience integrating and maintaining third-party data feeds or working with data licensing and data-sharing arrangements.
Practice with dbt or similar data transformation frameworks on Snowflake.

16 openings across locations