Data Engineer

We’re looking for a pragmatic and hands-on Full Stack Data Engineer to take end-to-end ownership of our data platform. A key part of this role is data democratisation: bringing trusted data to everyone at Coople in a way that is easy to use, discoverable, and consistent. As a data-driven organisation, we want to evolve to an environment where data is truly available “everywhere” and is a default input into day-to-day and strategic decisions.

Our core stack includes Databricks (Data Lake) and Power BI (reporting). The next step is to evolve our data development environment and data stack into an AI-first setup: we want to use AI wherever it creates leverage (development, testing, documentation, data quality checks, incident response, and stakeholder enablement), and continuously optimize our stack and ways of working for faster, safer delivery.

To make data accessible, we also want to enable conversational access to data (a chat interface for metrics, definitions, and insights) so that non-technical stakeholders can reliably get answers fast, with clear context and trust signals. You will work closely with development teams and stakeholders in Warsaw (partly in person/hybrid) and you’ll often act as the “glue” between product engineering, business users, and clients in other locations too.

The skills we're looking for in the ideal candidate:

• Around 5 years of experience with strong data engineering fundamentals: SQL, data modelling, ETL/ELT patterns, and operating data pipelines in production
• Databricks experience is a must (Spark/Delta, notebooks, jobs/workflows, Delta Lake concepts) and building/operating a Data Lake
• Power BI knowledge is a must (data modelling, measures, performance considerations, and stakeholder-facing reporting)
• Strong engineering standards: CI/CD, testing strategies, observability, performance tuning, and production readiness for data pipelines
• Experience owning data end-to-end: ingestion, transformations, data quality, and delivery to business-facing artifacts
• Experience enabling data democratisation (self-service, documentation, metric definitions, and usability for non-technical stakeholders) and interest in conversational data experiences (chat-based access to trusted metrics, definitions, and insights)
• AI-first development mindset: comfortable using AI tools to speed up delivery (e.g., code generation, review, test creation, documentation) and strong judgment on validation, correctness, and safety
• Fluent English