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Senior Data Engineer

Vitrolife
CompanyVitrolife
CategoryEngineering
Location
Remote
EmploymentNot stated
LevelSenior
SalaryNot stated by the employer
Posted18 Jun 2026
Last verified30 Jul 2026
SourceEmployer career page (teamtailor)
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Description
At the Vitrolife Group, we work every day to unlock the full potential of science and technology to reduce the barriers towards building a family. Together we help our customers and their patients to fulfill the dream of having a healthy baby. Vitrolife Group is a global provider of medical devices and genetic services. Based on science and advanced research capabilities, we develop services and products for personalized genetic information and medical device products. We support our customers by improving their clinical practice for the patient's outcome of fertility treatment. Shape the Platform, Enable Domains, Build for Scale We are looking for a Senior Data Engineer to join our Group Analytics enabling team. This is a key role in establishing and evolving our global data platform, with Microsoft Fabric and the Azure ecosystem as the primary technology direction. You will combine hands-on data engineering with architectural responsibility, helping us build scalable, governed, and automated data platform capabilities. The role is central to our ambition to move from fragmented and manually maintained legacy solutions toward a modern, domain-oriented data platform that enables trusted analytics, self-service, and future AI/ML use cases. This is an opportunity for someone who enjoys building for scale, setting technical direction, and enabling others through strong engineering standards, reusable patterns, and practical guidance. Location: Gothenburg, Sweden or Valencia, Spain Your Mission As a Senior Data Engineer, you will help design, build, and mature our global data platform. You will work with Microsoft Fabric, lakehouse and medallion architecture, reusable data pipelines, analytical data models, and modern engineering practices. You will play an important role in enabling a federated, data mesh-inspired operating model, where domain teams can own and evolve their data products within clear technical and governance guardrails. Depending on your profile, you may also take architectural responsibility for selected platform capabilities, patterns, and technical decisions. Experience from other modern lakehouse platforms, such as Databricks, Spark, or PySpark, is highly relevant where it strengthens your ability to design scalable and automated data solutions. What You’ll Do Help design, build, and evolve our Microsoft Fabric-based global data platform, including scalable pipelines, lakehouse patterns, and analytical data models. Develop reusable engineering standards, templates, and governed data objects that enable domain teams to build and manage data products. Apply modern engineering practices such as Git, CI/CD, monitoring, documentation, testing, and infrastructure-as-code principles such as Terraform. Embed security, access control, GDPR/PII handling, lineage, and metadata requirements into platform delivery. Work closely with enterprise architects, data engineers, data analysts, data scientists, business stakeholders, and domain teams. Mentor colleagues and support the modernization and deprecation of legacy BI/DW solutions. What You Bring Senior-level data engineering experience with strong hands-on delivery, architectural understanding, and ability to design scalable platform solutions. Strong SQL and Python skills, with Microsoft Fabric experience or transferable lakehouse expertise from Databricks, Spark, PySpark, or Delta Lake. Experience with production-grade data pipelines, medallion/lakehouse architecture, analytical data modeling, and domain-oriented data design. Experience with modern engineering practices such as Git, CI/CD, DevOps, monitoring, and preferably infrastructure-as-code principles such as Terraform. Good understanding of data governance, metadata, lineage, access control, GDPR, and PII handling. Collaborative mindset, with the ability to create reusable patterns and
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