Senior Technical Product Manager – Human Biology

Description

The company is a global partner for AI-first digital transformation and engineering, with over 25 years of experience and about 5,000 people across 16 countries. It designs and builds scalable products, platforms and data-driven solutions.

Its work covers artificial intelligence, data and cloud, intelligent automation and digital products.

The CEE region team of nearly 1,000 builds modern applications, data platforms and AI solutions for large clients across many industries, using AWS, Azure, GCP, Databricks and Snowflake. The team blends engineering depth with a consulting approach and shares knowledge continuously.

The company is hiring a Senior Technical Program Manager for its Life Sciences R&D product team. The role supports the digital transformation of a leading pharmaceutical company.

You will lead strategic technical programs and product portfolios for researchers, cell biologists, computational biologists and data scientists. You will work with product, engineering, data, AI/ML and scientific teams, turning complex scientific needs into scalable technical solutions and guiding work from discovery and requirements through to launch.

The role blends program management, product and backlog ownership, an understanding of cloud and data platforms, and deep knowledge of human biology and life sciences.

Responsibilities

• Own and prioritize backlogs across several technical workstreams, such as human biological data repositories, analytical pipelines, and search and visualization platforms.
• Govern strategic programs across the product development lifecycle, from strategy and requirements validation through architecture review to launch.
• Turn scientific and business requirements into clear user stories, acceptance criteria, product development plans and actionable technical requirements.
• Coordinate dependencies between data engineering, platform engineering, UI/UX, AI/ML and scientific knowledge engineering teams.
• Lead continuous discovery, user research and feedback loops with scientists and R&D stakeholders to shape the roadmap.
• Define and maintain data models, metadata standards, FAIR data requirements and data governance practices with scientific and data teams.
• Make sure security, compliance, data provenance and traceability are addressed at every stage of the product lifecycle.
• Work with Project Managers and Product Owners on scope, priorities, resource allocation, risks and cross-team dependencies.
• Lead UAT, release decisions and launch readiness with technical, business and scientific stakeholders.
• Serve as the main contact between engineering teams, business stakeholders, scientific users and external partners.
• Run requirements workshops, discovery sessions, design reviews and cross-functional delivery meetings.
• Present technical, product and delivery updates to senior stakeholders and governance forums.
• Use Jira, Confluence and Jira Product Discovery to manage backlogs, requirements, documentation and traceability.
• Work with engineering and infrastructure teams on cloud architecture, APIs, distributed data flows and scientific data ingestion.
• Use GCP services and modern data engineering practices to support scalable scientific data platforms.
• Find opportunities for AI and automation in program management, requirements, documentation and scientific workflows.
• Help identify and deliver production AI use cases with client teams.
• Drive ongoing platform improvement, modernization, technical debt reduction and cost optimization.
• Coordinate external vendors and technology partners where needed.

Requirements

• At least 8 years in technical program management, product management, technical delivery or a similar role, ideally on cloud-based data platforms or scientific informatics systems.
• Proven experience leading large cross-functional programs with several engineering teams and business or scientific stakeholders.
• Strong background in life sciences, biopharma, biotech or a closely related scientific field.
• You can communicate fluently with cell biologists, computational biologists, data scientists and engineers.
• Strong understanding of human biological data and multi-omics types such as transcriptomics/RNA-seq, proteomics and functional assays.
• Practical knowledge of FAIR data principles, biological ontologies, metadata standards and data governance.
• Experience in pharmaceutical or other highly regulated environments, with knowledge of GxP and/or 21 CFR Part 11.
• Strong technical background in software engineering, data engineering, technical architecture or platform development.
• Solid understanding of data pipelines, APIs, distributed systems, databases and modern cloud platforms.
• Hands-on GCP experience is required, including familiarity with BigQuery, Workflows, Vertex AI, Cloud Run and Google Cloud Storage.
• Experience managing systems that ingest, process, store and expose complex scientific or other large-scale datasets.
• Working knowledge of SQL and NoSQL databases and modern data engineering practices.
• Familiarity with AI/ML platforms and MLOps concepts.
• Strong understanding of Agile, Scrum and hybrid delivery models.
• Expert knowledge of Jira and Confluence, including experience maintaining complex backlogs and requirements traceability.
• Excellent skills in stakeholder management, communication, facilitation and conflict resolution.
• Strong analytical and strategic thinking, with the ability to work through complex and ambiguous requirements.
• Nice to have: experience with high-performance computing (HPC), large-scale data processing or HPC-to-cloud migration.
• Nice to have: knowledge of GCP architecture for large-scale scientific workloads and storage optimization.
• Nice to have: experience with biological research workflows, in vitro cell models, high-throughput phenomics or translational research.
• Nice to have: experience with human data governance, patient privacy, data reproducibility, lineage and audit readiness.
• Nice to have: experience with vendor management and multi-vendor delivery environments.
• Nice to have: relevant GCP certifications, such as Professional Cloud Architect or Professional Data Engineer.

Conditions

The recruitment process runs in stages: CV review, HR call, interview, client interview, then decision.