Staff Data Engineer

Staff Data Engineer OUR STORY: Every year millions of people are either filing their taxes in fear or giving up on their tax refund altogether. We're working on fixing that. Our intuitive app enables anyone, regardless of education or background, to file their taxes with newfound confidence. Spread across Germany, Spain and the UK, the team at Taxfix Group with its brands Taxfix and Steuerbot, is a compassionate group of solution-finders. We speak our minds openly, and with over 400 professionals, including tax experts, developers, and IT security experts, we're rich in ideas and voices. The group has facilitated more than 3.5 billion euros in tax refunds for its customers since its founding in 2016. YOUR CHALLENGE: Taxfix makes tax filing simple, fast, and accessible for millions of users across Europe. Behind the product sits a data platform that powers everything from business analytics and regulatory reporting to ML and AI-driven product features. We’re growing and the platform needs to grow with us. We are looking for an experienced Data Platform Engineer to design, build, and operate the infrastructure and pipelines that make data at Taxfix reliable, compliant, and ready for AI. You will own the systems that move data from operational databases, APIs, and SaaS tools into our analytical environment and make sure that data is correct, timely, and safe to use. Your work will directly enable ML and AI-powered product experiences, self-serve analytics, and regulatory reporting. This is a hands-on engineering role. You will write code, review designs, and operate production systems not just draw diagrams. YOUR TEAM: The Data Platform team is part of the Data Organization, which enables everyone at Taxfix to make data-driven decisions, drive business growth, and power ML and automation in our products. Within our group we have product analysts, analytics engineers, machine learning engineers, and data engineers working across the whole company. The platform team serves many consumers analytics, ML, product, and compliance so you can expect to join cross-functional project teams regularly, working alongside backend and frontend engineers, analysts, ML engineers, product and design. Team members are all data engineers but from different backgrounds. We rely on each other to deliver our best, grow together, share knowledge openly, and invest in personal development through mentoring and innovation. YOUR RESPONSIBILITIES AND DECISIONS - Build and maintain ingestion pipelines that capture changes from application databases, APIs, SaaS and deliver clean, analytics-ready tables to our cloud data warehouse - Design data models with proper layering that handle real-world data complexity: out-of-order events, schema evolution, late arrivals, and backfills - Own and evolve cloud platform infrastructure — manage GCP resources (GCS, Dataflow, Dataproc), provision and maintain environments with Terraform, and ensure the platform is cost-efficient and scalable - Own data quality monitoring — build validation, monitoring, and alerting that catches problems before downstream consumers do - Implement privacy and compliance controls — anonymization, pseudonymization, access policies, and deletion propagation (GDPR right-to-be-forgotten) across raw and derived layers - Prepare data for ML and AI use cases — build governed, privacy-safe datasets and feature pipelines that ML engineers and data scientists can use for model training, evaluation, and production inference - Operate and improve our orchestration layer — scheduling, retries, SLA tracking, and observability for data pipelines - Define and raise the bar on engineering standards — code quality, testing, CI/CD, documentation, and infrastructure-as-code - Evaluate and adopt new technologies that help the team achieve its goals across data management, analytics, and machine learning - Incorporate AI into platform services — enable AI-assisted development workflows and buil ... (truncated, view full listing at source)