Senior Data Platform / Data Engineer

About the roleWe are looking for a Senior Data Platform / Data Engineer to join our ML Platform team and help build and scale the data infrastructure that powers our AI products in dentistry. Our platform supports the full AI development lifecycle, from raw data ingestion and annotation workflows to dataset versioning and model training pipelines. You will work closely with Machine Learning Researchers (MLRs), MLOps engineers, and product teams to ensure our data infrastructure is reliable, scalable, and easy to use. A key focus of the role is improving our Data Lakehouse (DLH) and dataset management workflows, including dataset versioning (DVC) and improving how data is prepared, extracted, and consumed across research and production systems.What you will work on:Typical responsibilities include:Data platform ownershipDesign and evolve the Data Lakehouse (DLH) architecture used across our ML teams.Improve the reliability and structure of data ingestion, extraction, and transformation pipelines.Ensure datasets used for training and evaluation are consistent, reproducible, and well documented.Dataset lifecycle managementImprove workflows for dataset versioning and reproducibility using tools such as DVC.Design solutions for managing multiple versions of datasets and annotations across experiments and models.Improve the ability for researchers to retrieve the correct dataset versions reliably.Data pipelines and infrastructureBuild and maintain scalable data pipelines in Python.Improve metadata management, dataset validation, and data quality monitoring.Optimize data workflows across AWS-based llaboration with ML teamsWork closely with ML researchers and ML engineers to understand their data needs.Support research workflows with reliable and efficient data access patterns.Help translate research requirements into robust platform capabilities.Data governance and qualityImplement practices for data quality, reproducibility, and traceability across the ML lifecycle.Ensure our data infrastructure meets the requirements of regulated AI development.What we’re looking for:Must have:Strong Python engineering skillsExperience building data pipelines or data platformsExperience working with AWSExperience working with large datasets used in ML workflowsStrong software engineering practices (testing, CI/CD, documentation)Experience collaborating with ML teams or working in AI environmentsNice to have:Experience with dataset versioning tools such as DVCExperience with KubernetesExperience with data lakehouse architecturesExperience working with annotation pipelines or ML training datasetsExperience with Postgre SQL, Metabase, or similar data toolingExperience working in regulated environments (medical / healthcare AI)Our stackAWSPythonKubernetesPostgre SQLMetabaseDVC for dataset versioningInternal Data Lakehouse infrastructureAll qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability.Employment Type:Full TimeAlternative Locations:Spain: MadridTravel Percentage:0 - 10%Requisition ID:20071