We are looking for a hands-on Senior Data Engineer to act as the primary technical reference for building R&D; data products. The role sits at the intersection of scientific domain, data platform, and engineering delivery. You will guide technical design and implementation across data engineering, analytics, AI and application components within an R&D; data and AI ecosystem, while carrying accountability for engineering quality, mentoring and delivery outcomes. Provide hands-on technical expertise across R&D; data, analytics, AI and application components, guiding design and implementation from prototype through to validated production. Act as the technical escalation point for complex engineering challenges spanning data pipelines, analytics, AI services and full-stack applications. Own end-to-end technical design for data products: ingestion, modelling, curation, serving, and the consuming application or API layer. Make and document architecture decisions, including technology evaluation and integration into an existing large-scale data ecosystem. Ensure delivery commitments are met without trading away reliability, security, maintainability or data integrity. Align with enterprise and software architects so that squad-level implementation stays homogenous with the wider ecosystem. Lead code reviews and set engineering standards (branching strategy, testing expectations, definition of done, observability baseline). Ensure solutions meet data governance, security and compliance requirements relevant to regulated R&D; data.



Embed governance-by-design: lineage, cataloguing, access control, data quality rules and audit trail designed in from the start. Partner with data governance, platform and architecture teams on standards adoption. Bachelor's or Master's (or equivalent practical experience) in Computer Science, Data Engineering, Life Sciences, Bioinformatics or a related field. 3-5+ years in data engineering, analytics engineering, software engineering or AI platform roles. Deep, production-grade experience on a modern cloud data platform
- Databricks and/or Snowflake. A track record of shipping data products in pharma or biotech. Data modelling for analytical and product use
- dimensional, data vault, medallion/lakehouse patterns. CI/CD, automated testing (including data testing), infrastructure-as-code, observability, access management, cost awareness. comfort with the application layer that sits on top of the data (e.g. FastAPI, REST/GraphQL, containerised services). Full-stack familiarity (React/TypeScript). Metadata, catalog and data quality tooling; knowledge graphs for scientific data. FAIR data principles applied in practice. Experience with scientific data management platforms. Zifo is a general R&D; solutions provider focused on the industries of Pharma, Biotech, Manufacturing QC, Medical Devices, specialty chemicals and other research-based organizations. We search with a two-point agenda
- technical competency and cultural adaptability. #

📌 Senior Engineer, Data Engineering (La Coruña)
🏢 Zifo
📍 La Coruña