Senior Scientist, Bioinformatics Engineer

AstraZeneca plc; Województwo mazowieckie; Hybrid; PLN 150,000 - 190,000; Full time

Job summary

AstraZeneca is seeking a Senior Scientist - Bioinformatics Engineer in Warsaw, Poland, to advance proteomics data platforms and scalable computational workflows within QuBi. You will drive end-to-end pipeline development, integrate metadata and ensure FAIR data principles across projects.

The role combines bioinformatics, data engineering and software engineering practices, with opportunities to apply AI-enabled workflows and contribute to scalable, reproducible analytics for across therapeutic

Qualifications

• Ph.D. or Masters with 3 years in bioinformatics/computational biology or related field.
• Experience building reproducible analytical workflows for complex biological datasets.
• Experience with cloud platforms (AWS/Azure) and core concepts like VMs, storage and networking.
• Experience developing reproducible workflows with Nextflow or Snakemake and containerized Linux environments.
• Skilled in designing scalable omics data models and applying FAIR principles.
• Proficient in programming/data analysis with R and/or Python; familiar with software development best practices.
• Strong version control (Git) and collaborative development experience.
• Ability to work independently and across multidisciplinary teams.
• Strong communication skills for explaining complex concepts and enabling adoption of analyses.

Responsibilities

• Design, implement and maintain end-to-end pipelines for high-throughput proteomics data analysis.
• Develop portable, versioned workflows using Nextflow or Snakemake.
• Containerise environments with Docker and deploy across HPC and cloud settings.
• Incorporate QC, validation and provenance into workflows for reproducible outputs.
• Follow software engineering practices: Git, CI/CD, testing, docs and release management.
• Build interfaces and interfaces and ensure metadata/execution standards enable reuse by AI-enabled workflows.
• Develop scalable data models and storage strategies for raw data, intermediate results and outputs.
• Apply FAIR data principles and collaborate on governance and access control.
• Create data products and result databases using Snowflake, PostgreSQL and related tools.
• Develop scientific apps using R Shiny or Streamlit where appropriate.

Skills

Independent contributor

Communication

Cross-functional

Problem solving

Education

Ph.D. in bioinformatics or related

Masters + 3 years experience

Tools

Nextflow

Snakemake

Docker

Git

PostgreSQL

Snowflake

R

Python

AWS

Azure

Job description

Location: Warsaw, Poland Hybrid model of work: 3 days in office, 2 remote per week

At AstraZeneca, we are combining cutting-edge science, data, and artificial intelligence to transform how we discover and develop medicines. As part of Data Sciences and Quantitative Biology (QuBi) this role will work in close collaboration with a group of chemical biology and proteomics scientists and QuBi Bioinformaticians supporting therapeutic areas across AstraZeneca, offering a unique opportunity to contribute to and apply new digital and AI capabilities.

Based at Warsaw, Poland, you will work at the intersection of mass spectrometry-based (MS) proteomics and computational biology, helping to build the data platform and analytical foundations that allow scientists to explore high-throughput proteomics data from mass-spectrometer and emerging molecular assays. This is a hands-on technical role for someone who combines practical bioinformatics, workflow development, and data engineering skills with strong proteomics expertise to deliver robust, scalable workflows, data infrastructure, and tools that scientific teams can rely on.

What You Will Do

As Senior Scientist - Bioinformatics Engineer within QuBi, you will:

Workflow development and automation

• Design, implement and maintain reproducible end-to-end pipelines for the processing, analysis, interpretation and visualisation of high-throughput proteomics data.
• Develop portable and versioned computational workflows using technologies such as Nextflow, Snakemake or comparable workflow frameworks.
• Containerise analytical environments using technologies such as Docker and deploy workflows across HPC and cloud computing environments.
• Build robust quality control, validation and provenance into computational workflows to produce reproducible, interpretation-ready outputs.
• Apply software engineering best practices including version control, code review, automated testing, CI/CD, documentation and release management.
• Design workflows and analytical components with appropriate interfaces, metadata and execution standards to enable programmatic reuse, including by emerging AI-enabled and agentic scientific workflows.

Data management and infrastructure

• Develop and maintain scalable data models and storage strategies for proteomics raw data, intermediate results, processed datasets and analytical outputs.
• Establish metadata and provenance approaches that connect experimental context, sample information, analytical parameters, workflows and results.
• Integrate chemical biology, experimental and proteomics metadata to create harmonised, analysis-ready datasets that enable reuse and biological insight across studies.
• Apply FAIR data principles and appropriate data governance, access control and retention practices in collaboration with relevant technology and security teams.
• Contribute to searchable analytical data products and result databases using technologies such as Snowflake, PostgreSQL or equivalent platforms.
• Develop scientific interfaces and applications using technologies such as R Shiny, Streamlit or comparable frameworks where appropriate.
• Help make proteomics data and outputs discoverable, reusable and suitable for downstream advanced analytics, machine learning and AI applications.

Required Qualifications

• Ph.D. (or Masters with 3 years of experience) in bioinformatics, computational biology, computer science, or a related discipline
• Demonstrated experience in bioinformatics and data analysis, with the ability to develop and apply reproducible analytical workflows for complex biological datasets.
• Experience with cloud platforms (such as AWS or Azure), covering core concepts like virtual machines, storage buckets, and basic cloud networking.
• Experience developing reproducible computational workflows using Nextflow or Snakemake, together with containerised Linux environments.
• Experienced in designing scalable omics data models and in applying FAIR data principles and data governance.
• Experience with programming and data analysis in languages such as R and/or Python, and familiarity with scientific software development best practices.
• Proficiency with version control (Git/GitHub) and collaborative software development practices.
• Ability to work as an independent contributor while collaborating effectively across multidisciplinary teams.
• Strong communication skills, with the ability to explain complex scientific and technical concepts to diverse audiences and support adoption of analytical solutions.

Preferred Qualifications

• Experience in analyzing MS-based discovery proteomics data
• Experience developing or applying machine learning and AI for scientific data analysis, interpretation, or workflow automation.
• Experience in multi-omics analysis is a plus
• Solid grounding in the statistics of high-dimensional omics data
• A track record of scientific innovation demonstrated through publications, conference presentations, open-source contributions, software products, or deployed analytical tools in bioinformatics, AI, or data science.

How We Do It

At AstraZeneca,we'rededicated to being a Great Place to Work, where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit.There'sno better place to make a difference in medicine, patients, and society. An inclusive culture that champions diversity and collaboration. Always committed to lifelong learning, growth, and development.

Date Posted

30-paź-2026

Closing Date

20-lis-2026

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.