> Markdown version of [/jobs/ext/2667407-technical-lead-data-gcp](https://www.wearedevelopers.com/jobs/ext/2667407-technical-lead-data-gcp). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Technical Lead - Data GCP - **Company:** Gapstars - **Location:** ALMERE, Netherlands - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Automation of Tests, BigQuery, Software Quality, Continuous Integration, Data Flow Control, Python (Programming Language), Standard Sql, Google Cloud, SAP Integration Solutions, Git, Data Layers, Machine Learning Operations, Terraform, Software Version Control, Data Pipelines, Docker - **Published:** September 1, 2026 - **Apply:** https://gapstars.net/tech/career-listings/job-1620/ ## About the Role * Strong hands-on experience as a Data Engineer in production environments. * Strong Google Cloud Platform (GCP) experience is mandatory. * Strong experience with BigQuery. * Strong SQL and Python skills. * Experience building and operating scalable data pipelines. * Experience with dbt or similar transformation frameworks. * Understanding of data modeling and semantic layer concepts. * Experience with data quality, governance, security, and monitoring. * Experience with CI/CD and Git. * Strong stakeholder communication and ownership. Nice-to-Have * Experience with Dataflow, Cloud Run, Composer / Airflow, and GCS. * Terraform and Docker experience. * Experience with SAP integrations. * Experience supporting ML workflows or Data Science teams. * Experience with semantic modeling. * Experience with AI-enabled analytics. * Retail or e-commerce experience. ## Description As a Senior Data Engineer, you will design, build, and evolve scalable data products, pipelines, and data architectures on Google Cloud Platform (GCP). The role is strongly focused on GCP and requires hands-on experience building reliable data solutions that support analytics, reporting, machine learning, and business decision-making. You will also help establish engineering standards, improve data quality and governance, and work closely with technical and business stakeholders., 1) Data Engineering & Architecture * Design and evolve scalable data architectures on GCP. * Build and maintain reliable end-to-end data pipelines. * Develop and optimize data solutions using BigQuery, Dataflow, Cloud Run, Composer, and GCS. * Build reusable and well-structured data products for analytics and reporting. * Translate business requirements into scalable technical solutions. * Support integrations with enterprise platforms, APIs, SAP, and other data sources. 2) Data Transformation & Modeling * Develop transformation workflows using SQL, Python, and dbt. * Build and maintain reusable data models and semantic layers. * Establish standards for modeling, testing, documentation, and deployment. * Ensure datasets are analytics-ready and reusable across teams. 3) Data Quality, Governance & Reliability * Implement data quality controls, validation, reconciliation, and automated testing. * Ensure data remains accurate, secure, governed, and accessible. * Monitor pipeline health, freshness, performance, and operational stability. * Troubleshoot production issues and drive long-term improvements. * Contribute to governance standards around access, naming, lineage, and lifecycle management. 4) Platform Ownership & Engineering Standards * Contribute to infrastructure and deployment standards using Terraform, Docker, CI/CD, and Git. * Support secure access management and appropriate data permissions. * Promote engineering best practices around testing, code quality, documentation, and version control. * Mentor colleagues and support knowledge sharing within the team. 5) Collaboration & Communication * Work closely with Product Owners, Analysts, Data Scientists, Engineers, and business stakeholders. * Translate business requirements into practical technical solutions. * Communicate technical designs, risks, trade-offs, and progress clearly. * Take end-to-end ownership from requirements through production support., Technical Lead - Data GCP ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Backend Developer Salary in Germany [2023]](https://www.wearedevelopers.com/magazine/196-backend-developer-salary-in-germany-2023) - [Software Developer Salary in The Netherlands [2023]](https://www.wearedevelopers.com/magazine/217-software-developer-salary-in-the-netherlands-2023)