Data Engineer

Data Engineer (Midlevel) - TEKsystems Global Services (m/f/d) As a Data Engineer, you'll work closely with your manager and fellow engineers to establish a modern data platform and help shape how data is used across the organisation. You'll work closely with our Senior Engineering Manager, Data Platform, the BI team and our engineering teams who will produce data for and consume data from, your pipelines every day. The data platform team is brand new, so you'll help set up not just the architecture, but also the tools and ways of working around them. We haven't locked in our stack yet, which means your input on choices like the data warehouse or orchestration tool actually counts — and carries real weight given your experience. It's a small team, so you'll see the direct result of your work and help shape how things get done from day one. You'll join as one of the first hires in our new Data Platform team, helping to shape the foundations, build core pipelines, and establish best practices for the future. What we are looking for: • You have 3-5 years of experience building and maintaining data pipelines and data platforms. • You're curious about architecture decisions and want to contribute to technical discussions, not just deliver tickets. • You see data quality as an essential part of the solution rather than something to add later. • You've worked on a platform implementation, migration, or modernisation project and understand the challenges that come with change. • You can explain technical concepts clearly to both technical and non-technical stakeholders. • You enjoy building practical solutions that deliver value and can evolve over time. What You'll Do • Help evaluate and choose the tools for our data stack: data warehouse, ELT, and orchestration — and make architecture-level calls together with your manager, not just implement someone else's design. • Build and maintain data pipelines, and mentor and unblock your peer day-to-day, without formal management responsibility. • Add data quality checks to every pipeline change: null checks, row counts, schema validation, and dbt tests (or equivalent) as standard practice, not an extra step. • Break your work into small, deployable increments and keep pull requests focused. • Monitor pipeline outputs after every deployment and keep the codebase easy to work with. • Respond quickly to pipeline failures, investigate the root cause, and escalate when an issue is bigger than the two of you. • Review pull requests with constructive feedback, pair with your peer on complex or unfamiliar work, and help set the technical bar the team grows on. • Communicate early when changes affect downstream consumers such as BI, ML, or customers, and prioritize based on customer impact. • Share what you've learned from past platform builds — including what you'd do differently — and help translate that into how this team works. Ready to take the next step in your Data Engineering career? Join a team where your ideas matter, your impact is visible, and you'll help shape a modern data platform that powers real business decisions. Apply today and grow alongside experienced engineers in an environment that values collaboration, innovation, and continuous learning.