Qiagen

Senior Data Engineer – Biomedical Knowledge Graphs

Cluj-Napoca

Actively hiring, first seen by us 2 days ago

Pay: Pay not listed
Work setting: Not stated
Employment: Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting

Own the end-to-end build and release cycle for knowledge base products
Develop and maintain pipelines turning RDF content into graph and tabular datasets
Validate biomedical datasets and analyse release-to-release changes
Diagnose pipeline and data issues, tracing them to source
Build Python and/or Java solutions, quality checks and CI/CD pipelines

From the employer’s posting

Owning the end-to-end build and release cycle for biomedical knowledge base products

Developing and maintaining production pipelines that transform curated RDF content into graph databases, analytical datasets and tabular exports

Investigating and validating complex biomedical datasets using SPARQL and RDF, Neo4j and Cypher, and SQL, analysing release-to-release changes

Diagnosing and resolving data and pipeline issues, tracing problems to their source

Building and improving well-tested Python and/or Java solutions, automated quality checks, build scripts and CI/CD pipelines

Education & alternatives

Your profile - MSc or PhD in Data Science, Computer Science, Bioinformatics, Computational Biology or a related discipline, or equivalent relevant professional experience, combined with 5+ years of experience developing production data pipelines, scientific data products or knowledge-based applications. - Strong programming skills in Python and/or Java, together with solid SQL capabilities and experience writing maintainable, well-tested production code.

Benefits in the posting

Full benefits wording

Bonus/Commission
Local benefits
Referral Program
Volunteer Day
Employee Assistance Program

From the employer’s posting.

About Qiagen

Join QIAGEN Digital Insights in Cluj-Napoca and help transform complex biomedical data into actionable scientific knowledge.

In the employer’s words · Read in context

Apply at Qiagen

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records: Live
First seen by us: Nov 11, 20262 days ago
Recorded sightings: 3
Last seen by us: Nov 13, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 2

Early. Similar jobs usually come down between day 6 and day 56.

From 13,630 similar postings that came down. Coming down is not always a hire.

Qiagen is hiring

9 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Java
Python
R
SQL
AWS
Docker
Neo4j

Where the posting names them

- Diagnosing and resolving data and pipeline issues, tracing problems to their source and collaborating with content specialists to determine whether changes should be addressed in the source knowledge base or within the build. - Building and improving well-tested Python and/or Java solutions, automated quality checks, build scripts and CI/CD pipelines using test-driven development, code review and modern software engineering practices. - Collaborating with bioinformatics, content, DevOps and data platform teams while continuously automating manual processes and improving the reliability, quality and efficiency of knowledge base releases. Triaging failing content tests to decide whether a release can safely proceed will also be part of your role.

- MSc or PhD in Data Science, Computer Science, Bioinformatics, Computational Biology or a related discipline, or equivalent relevant professional experience, combined with 5+ years of experience developing production data pipelines, scientific data products or knowledge-based applications. - Strong programming skills in Python and/or Java, together with solid SQL capabilities and experience writing maintainable, well-tested production code. - Hands-on experience with knowledge graphs or graph data technologies, particularly RDF and SPARQL and/or Neo4j and Cypher, with an interest in expanding your expertise across these technologies.

- Strong communication and collaboration skills, with an interest in working across data science, software engineering and scientific disciplines in an international environment. - Experience in one or more of the following would be advantageous: biomedical or biological data, genes and pathways, biomedical ontologies, knowledge graphs, NLP or LLM-based applications, MCP servers, R, Python or R package development, Docker, or infrastructure as code using AWS CDK. What we offer

- Owning the end-to-end build and release cycle for biomedical knowledge base products, from transferring curated content to the cloud and running pipelines through to ingestion, deployment and production release. - Investigating and validating complex biomedical datasets using SPARQL and RDF, Neo4j and Cypher, and SQL, analysing release-to-release changes and identifying significant shifts, inconsistencies or quality issues. - Developing and maintaining production pipelines that transform curated RDF content into graph databases, analytical datasets and tabular exports, ensuring they remain reliable as schemas and source data evolve.

- Hands-on experience with knowledge graphs or graph data technologies, particularly RDF and SPARQL and/or Neo4j and Cypher, with an interest in expanding your expertise across these technologies. - Practical experience with AWS, CI/CD and build automation, using technologies such as Jenkins, Gradle, GitHub Actions or Maven, alongside Git-based source control and code review workflows. - A methodical approach to data validation, quality assurance and reproducible production processes, with the ability to investigate complex datasets, identify anomalies and improve multi-step workflows.

- Strong programming skills in Python and/or Java, together with solid SQL capabilities and experience writing maintainable, well-tested production code. - Hands-on experience with knowledge graphs or graph data technologies, particularly RDF and SPARQL and/or Neo4j and Cypher, with an interest in expanding your expertise across these technologies. - Practical experience with AWS, CI/CD and build automation, using technologies such as Jenkins, Gradle, GitHub Actions or Maven, alongside Git-based source control and code review workflows.

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Overview 

At QIAGEN, we are driven by a simple but powerful vision: making improvements in life possible.

We’re dedicated to revolutionizing science and healthcare for the better. From our entrepreneurial roots to our current global presence, we've grown into a force for positive change. With thousands of employees across six continents, collaboration is our greatest strength. We’re always striving to identify talented individuals to join our exceptional teams.

We have played a pivotal role in shaping modern science and healthcare, and we're just getting started. If you're someone who thrives on new challenges, values diversity and wants to make a tangible difference in people's lives, then QIAGEN is the place for you.

At QIAGEN, every day is an opportunity to make a real-life impact.

Join us, grow with us, and together, let's shape the future of biological discovery.

‎

About the opportunity

Join QIAGEN Digital Insights in Cluj-Napoca and help transform complex biomedical data into actionable scientific knowledge. Our solutions, including OmicSoft, Discovery Knowledge Base, Ingenuity Pathway Analysis (IPA) and QCI, enable pharmaceutical, biotech, academic and government researchers to interpret molecular and genomic data.

As a Senior Data Scientist – Biomedical Knowledge Graphs, you will own the development, validation and release of biomedical knowledge base products supporting scientists and AI-enabled applications. Working with curated RDF content, knowledge graphs and analytical databases, you will build robust pipelines that transform biological knowledge into graph, analytical and tabular formats. Combining data science, knowledge graph technologies and software engineering, you will also work with AI-extracted relationships and LLM-enabled tools, collaborating with content specialists, bioinformaticians, DevOps and data platform engineers.

Your tasks include

Owning the end-to-end build and release cycle for biomedical knowledge base products, from transferring curated content to the cloud and running pipelines through to ingestion, deployment and production release.
Investigating and validating complex biomedical datasets using SPARQL and RDF, Neo4j and Cypher, and SQL, analysing release-to-release changes and identifying significant shifts, inconsistencies or quality issues.
Developing and maintaining production pipelines that transform curated RDF content into graph databases, analytical datasets and tabular exports, ensuring they remain reliable as schemas and source data evolve.
Integrating AI-extracted biomedical relationships with curated knowledge and supporting MCP servers and client libraries that enable users and LLM-based applications to interact with the knowledge base.
Diagnosing and resolving data and pipeline issues, tracing problems to their source and collaborating with content specialists to determine whether changes should be addressed in the source knowledge base or within the build.
Building and improving well-tested Python and/or Java solutions, automated quality checks, build scripts and CI/CD pipelines using test-driven development, code review and modern software engineering practices.
Collaborating with bioinformatics, content, DevOps and data platform teams while continuously automating manual processes and improving the reliability, quality and efficiency of knowledge base releases. Triaging failing content tests to decide whether a release can safely proceed will also be part of your role.

Your profile

MSc or PhD in Data Science, Computer Science, Bioinformatics, Computational Biology or a related discipline, or equivalent relevant professional experience, combined with 5+ years of experience developing production data pipelines, scientific data products or knowledge-based applications.
Strong programming skills in Python and/or Java, together with solid SQL capabilities and experience writing maintainable, well-tested production code.
Hands-on experience with knowledge graphs or graph data technologies, particularly RDF and SPARQL and/or Neo4j and Cypher, with an interest in expanding your expertise across these technologies.
Practical experience with AWS, CI/CD and build automation, using technologies such as Jenkins, Gradle, GitHub Actions or Maven, alongside Git-based source control and code review workflows.
A methodical approach to data validation, quality assurance and reproducible production processes, with the ability to investigate complex datasets, identify anomalies and improve multi-step workflows.
Strong communication and collaboration skills, with an interest in working across data science, software engineering and scientific disciplines in an international environment.
Experience in one or more of the following would be advantageous: biomedical or biological data, genes and pathways, biomedical ontologies, knowledge graphs, NLP or LLM-based applications, MCP servers, R, Python or R package development, Docker, or infrastructure as code using AWS CDK.

What we offer 

Bonus/Commission

Local benefits

Referral Program

Volunteer Day

Internal Academy (QIALearn)

Employee Assistance Program

Hybrid work (conditional to your role)

Our people are the heartbeat of everything we do. Passion drives us as we push boundaries to innovate and evolve. We inspire with our leadership and make an impact with our actions. We cultivate a collaborative, supportive environment where each individual and team can flourish. We champion accountability and encourage entrepreneurial thinking.  

QIAGEN is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, or disability. 

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