Capgemini

Global consulting, technology services, outsourcing

Data Harmonization Engineer - Life Sciences

Data Management +1Updated on Nov 11

Full-timeNo salary listed

About the Job

Requirements

MSc or PhD, or equivalent professional experience, in biology, biomedical sciences, bioengineering, genetics, neuroscience, bioinformatics, computational biology, or a related field.
Three to five years of experience in data engineering, bioinformatics, or scientific data work with biomedical datasets.
Strong Python, including pandas or similar, and SQL skills, with experience building and maintaining pipelines.
Hands-on experience with data harmonization and mapping, vocabulary alignment, and persistent identifiers.
Experience with data quality assessment and validation frameworks, including checks written as code.
Solid Git practice, including branches, pull requests, and meaningful commit history.
Biological reasoning about data such as genes, variants, diseases, phenotypes, and assays.
Fluent English.
Clear communication with scientific and technical stakeholders.

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, including completeness, validity, consistency, uniqueness, and provenance checks.
Normalize entities such as genes, diseases, phenotypes, compounds, and 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.

Desired Qualifications

Experience with biomedical ontologies and databases such as Gene Ontology, MONDO, HPO, EFO, UBERON, ChEBI, Ensembl, or UniProt.
Agentic AI experience, including LLM-based agents or workflows, tool use, retrieval-augmented generation, or LLM-assisted curation and mapping, with validation of the output.
Experience with validation frameworks such as Great Expectations, Pandera, or SHACL.
Experience with workflow orchestration tools such as Airflow, Prefect, Snakemake, or Nextflow, and Docker.
Cloud platform experience with AWS, Azure, or GCP.
Knowledge of schema modelling such as LinkML or equivalent, FAIR principles, RDF, or SPARQL.
Applied machine learning.
Experience in pharma, biotech, or another regulated research environment.
Portuguese fluency.

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.

About the Company

Capgemini

Global consulting, technology services, outsourcing

Capgemini provides consulting, technology services, and outsourcing to help organizations transform digitally. Its offerings include strategy and transformation consulting, system integration, application development, IT infrastructure management, and managed IT operations. It differentiates itself with a global presence in over 50 countries and a focus on applying AI, cloud, and cybersecurity to real business problems. Its goal is to help clients navigate digital transformation and improve efficiency and innovation through tailored, contract-based or managed services.

Company size: 10,001+
Company stage: IPO
Headquarters: Paris, France
Founded: 1967

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