Real-World Data Analytics Engineer | OMOP/FHIR Pipelines

F. Hoffmann-La Roche AG

Madrid

Híbrido

EUR 70.000 - 100.000

Jornada completa

14 días+

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Descripción de la vacante

F. Hoffmann-La Roche AG in Madrid seeks a Real World Data Analytics Engineer to join our medical informatics team and translate analytics needs into scalable data pipelines for OMOP and FHIR mappings.

You will collaborate with clinicians, data scientists and IT to design, test ETL/ELT pipelines, apply tests to data pipelines, and ensure data semantics are preserved across models and use cases. English communication is essential in a multinational setting.

Formación

Bachelor’s or Master’s degree in computer science, data science or informatics.
Hands-on experience with healthcare data, especially OMOP.
Experience with terminology integration, including OHDSI Athena and UMLS.
Experience with LLMs or NLP frameworks for extracting structured data from unstructured clinical text to feed into OMOP/FHIR models.
Familiarity with context-aware AI tools, such as the Model Context Protocol, and prompt engineering for data discovery or code generation tasks.
Experience with AI-augmented data quality tools or ML-based anomaly detection for monitoring data pipelines and identifying semantic drift.
Hands-on experience with relational databases and cloud platforms such as Snowflake (Preferred).
Experience with graph databases such as Neo4j and GraphQL (Preferred).
Experience with SDTM SQL, Python (numpy, pandas, etc.) or R.
Strong software engineering background including test-driven development, OO programming, FP, CI/CD, git.
Excellent verbal and written communication skills in English.
Experience working with IT/technical development teams and translating between business needs and technical requirements.
Ability to work with minimal supervision, exercising discretion and independent judgment.
Ability to build collaboration and positive relationships in an agile, multinational organisation.

Responsabilidades

Syntactically and semantically map data to/from RWD common data models (e.g., OMOP, FHIR) using dbt or similar tools.
Design, develop, and test ETL/ELT pipelines for real‑world data.
Provide complete documentation and communication of all processes, methods, and results.
Integrate vocabularies/terminologies using REST APIs and/or via relational tables.
Co‑create scalable approaches for mapping data using declarative and functional programming approaches.
Understand the complexities of RWD use cases from both business and IT/technical perspectives and develop a strategic approach to balance short‑term benefits and long‑term costs.
Contribute and share learnings throughout RWD communities, particularly product teams looking to leverage RWD.
Act as a strategic partner to business and research stakeholders, translating complex clinical objectives into actionable, high‑quality data product requirements.
Partner with IT business domain leadership to influence product roadmaps.
Serve as an ambassador of medical informatics and highlight the importance of clinical terminology management to business stakeholders, IT business domains and senior leadership.