Data Engineer

Data sits at the heart of every digital product, analytics workflow, and AI initiative. As companies push more of these capabilities into production, the integrations that move and expose that data need to be solid. Datashift is looking for a Data Engineer to build and own those integrations.

Do you have strong Python skills, a genuine DevOps mindset, and a track record of shipping things that hold up in production? Do you feel at home across software engineering, data engineering, and operations?

You’re a practical engineer who takes pride in what ends up running in production. You care about reliability, security, and building APIs that other teams can count on.

Responsibilities

• Own the full lifecycle of Data Integration. Build them in Python with Databricks, Azure Function Apps, and other Azure services, translating requirements into clean, maintainable code;
• Keep APIs production ready. Performance, security, access control, observability, and cost all fall in your scope;
• Move legacy data APIs onto the platform’s current architectural standards and add structured logging and alerting so issues surface before users notice them;
• Own the CI/CD setup in Azure DevOps. Build pipelines that carry code through testing and deployment without manual steps;
• Work with the Data Engineering & Platform team and engineers across teams and countries to shape, ship, and document integrations end to end;
• Support the team with data engineering tasks where needed.