Data Harmonization Engineer (Life Sciences)

Capgemini Engineering; Porto; Ibrido; EUR 42.000 - 66.000; Tempo pieno

Vantaggi offerti da questo lavoro

Health and life insurance

Hybrid work

Training and certifications

Referral program with bonuses

Great office locations

Descrizione del lavoro

CAPGEMINI ENGINEERING in Porto seeks a data engineer to design and run Python and SQL pipelines, map messy multi-source data to canonical models, and ensure data quality for analytics, knowledge graphs and AI use cases.

You will work with scientists and engineers to translate scientific needs into data requirements, document mappings, and mentor junior colleagues while contributing to data harmonization and vocabularies with persistent identifiers.

Competenze

• MSc or PhD (or equivalent) in biology, biomedical sciences, bioengineering, genetics, neuroscience, bioinformatics or related field.
• 3–5 years of experience in data engineering, bioinformatics or scientific data work with real biomedical datasets.
• Strong Python (pandas or similar) and SQL skills, with pipelines you built and maintained.
• Hands-on experience with data harmonization & mapping, vocabulary alignment and persistent identifiers.
• Experience with data quality assessment and validation frameworks, with checks written as code.
• Solid Git practice & branches, pull requests, meaningful commit history.
• Biological reasoning about the data you handle (genes, variants, diseases, phenotypes, assays).
• Clear communication with scientific and technical stakeholders.
• Fluent English.
• Preferred qualifications: extensive biomedical ontologies, agentic AI, validation frameworks, workflow orchestration, cloud platforms, FAIR/RDF/SPARQL, ML, regulated environments, Portuguese fluency.

Mansioni

• Build and maintain Python and SQL pipelines for data manipulation, transformation and integration across multiple sources.
• Define and implement source-to-canonical mappings, persistent identifiers and vocabulary alignment.
• Design and automate data quality assessment: completeness, validity, consistency, uniqueness and provenance checks.
• Normalize entities (genes, diseases, phenotypes, compounds, tissues) against authoritative identifiers and ontologies.
• Work with scientists, data engineers and product teams to translate scientific needs into data requirements.
• Document mappings, modelling decisions and validation rules, and keep them in version control.
• Investigate and resolve data issues at the source, and communicate their impact.
• Mentor junior colleagues and review their code and mappings.

Conoscenze

Python (pandas) & SQL

Data harmonization & mapping

Data quality assessment

Git version control

Biology / bioinformatics background

Communication with stakeholders

Fluent English

Team mentoring

Formazione

MSc or PhD in biology / biomedical sciences / bioengineering or related field

Strumenti

Airflow

Snakemake

Nextflow

Docker

SQL

Git

Schema modelling (LinkML)

Descrizione del lavoro

CAPGEMINI ENGINEERING

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

CAPGEMINI ENGINEERING

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

YOUR ROLE

You will design and run pipelines that map messy, multi-source data to canonical models, standard identifiers and controlled vocabularies, and you will make sure the result is trustworthy, documented and ready for analytics, knowledge graphs and AI use cases. You are the person scientists and data engineers rely on to turn raw data into something they can query and trust.

Key responsibilities

• Build and maintain Python and SQL pipelines for data manipulation, transformation and integration across multiple sources
• Define and implement source-to-canonical mappings, persistent identifiers and vocabulary alignment
• Design and automate data quality assessment: completeness, validity, consistency, uniqueness and provenance checks
• Normalize entities (genes, diseases, phenotypes, compounds, tissues) against authoritative identifiers and ontologies
• Work with scientists, data engineers and product teams to translate scientific needs into data requirements
• Document mappings, modelling decisions and validation rules, and keep them in version control
• Investigate and resolve data issues at the source, and communicate their impact
• Mentor junior colleagues and review their code and mappings

YOUR PROFILE

• MSc or PhD (or equivalent professional experience) in biology, biomedical sciences, bioengineering, genetics, neuroscience, bioinformatics, computational biology or a related field
• 3 to 5 years of experience in data engineering, bioinformatics or scientific data work, with real biomedical datasets
• Strong Python (pandas or similar) and SQL skills, with pipelines you built and maintained
• Hands-on experience with data harmonization & mapping, vocabulary alignment and persistent identifiers
• Experience with data quality assessment and validation frameworks, with checks written as code
• Solid Git practice & branches, pull requests, meaningful commit history
• Biological reasoning about the data you handle (genes, variants, diseases, phenotypes, assays)
• Clear communication with scientific and technical stakeholders
• Fluent English
• Preferred qualifications:
• Experience with biomedical ontologies and databases such as Gene Ontology, MONDO, HPO, EFO, UBERON, ChEBI, Ensembl or UniProt
• Agentic AI experience & LLM-based agents or workflows, tool use, retrieval-augmented generation, or LLM-assisted curation and mapping, with validation of the output
• Validation frameworks (Great Expectations, Pandera, SHACL or similar)
• Workflow orchestration (Airflow, Prefect, Snakemake, Nextflow) and Docker
• Cloud platform experience (AWS, Azure or GCP)
• Knowledge of schema modelling (LinkML or equivalent), FAIR principles, RDF or SPARQL
• Applied machine learning
• Experience in pharma, biotech or another regulated research environment
• Portuguese fluency
• What we look for:
• Scientific curiosity paired with engineering discipline
• Critical thinking and attention to data provenance and quality
• Comfort with ambiguity, and the ability to move between scientific meaning and technical implementation
• An impact-driven mindset in a fast-paced environment

What You'll Love About Working Here

• Join a multicultural and inclusive team environment.
• Enjoy a supportive atmosphere promoting work-life balance.
• Engage in exciting national and international projects.
• Hybrid work.
• Your career growth is central to our mission. Our array of career growth programs and diverse professionals are crafted to support you in exploring a world of opportunities.
• Training and certifications programs.
• Health and life insurance.
• Referral program with bonuses for talent recommendations.
• Great office locations.

About Capgemini

Capgemini is the business transformation partner for enterprises in the age of AI. We help organizations imagine and build an intelligent, sustainable future, combining AI, technology and human ingenuity to transform how they operate, innovate and grow. With unique end-to-end capabilities spanning strategy, technology, engineering and intelligent operations, we bring together deep industry expertise and market-leading capabilities in AI, cloud and data to turn ambition into measurable business outcomes at scale. Supported by a robust ecosystem of partners and nearly 60 years of expertise, Capgemini is a responsible and diverse global organization of over 410,000 team members in more than 50 countries.