Senior Technical Product Manager - Human Biology

ph3Senior Technical Product Manager – Human Biology /h3 pXebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. /p pWe specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture. /p pIn the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. /p pWe are looking for a Senior Technical Program Manager to join our Life Sciences RD product team and support the digital transformation of a leading pharmaceutical company. /p pIn this role, you will lead strategic technical programs and portfolios of applications supporting researchers, cell biologists, computational biologists, and data scientists. You will work across product, engineering, data, AI/ML, and scientific teams, translating complex scientific needs into scalable technical solutions and driving delivery from discovery and requirements through launch. /p pThe role combines strategic program management, product and backlog ownership, technical understanding of cloud and data platforms, and strong knowledge of human biology and life sciences. /p h3You will: /h3 ul liown and prioritize product backlogs across multiple technical workstreams, including human biological data repositories, analytical pipelines, and search and visualization platforms, /li lilead strategic programs through product development lifecycle governance, from strategy and requirements validation through architecture review and launch, /li litranslate complex scientific and business requirements into clear user stories, acceptance criteria, product development plans, and actionable technical requirements, /li licoordinate dependencies across data engineering, platform engineering, UI/UX, AI/ML, and scientific knowledge engineering teams, /li lidrive continuous discovery, user research, and feedback loops with scientists and RD stakeholders to shape product roadmaps, /li lidefine and maintain data models, metadata standards, FAIR data requirements, and data governance practices together with scientific and data teams, /li liensure security, compliance, data provenance, and traceability requirements are addressed throughout the product lifecycle, /li licollaborate with Project Managers and Product Owners on scope, priorities, resource allocation, risks, and cross-team dependencies, /li lidrive UAT, release decisions, and launch readiness across technical, business, and scientific stakeholders, /li liact as a primary point of contact between engineering teams, business stakeholders, scientific users, and external partners, /li lifacilitate requirements workshops, discovery sessions, design reviews, and cross-functional delivery meetings, /li lipresent technical, product, and delivery updates to senior stakeholders and governance forums, /li liuse Jira, Confluence, and Jira Product Discovery to manage backlogs, requirements, documentation, and traceability, /li lipartner with engineering and infrastructure teams on cloud architecture, APIs, distributed data flows, and scientific data ingestion, /li lileverage GCP services and modern data engineering capabilities to support scalable scientific data platforms, /li liidentify opportunities for AI and automation across program management, requirements, documentation, and scientific workflows, /li lisupport the identification and delivery of production AI use cases together with client teams, /li lidrive continuous platform improvement, modernization, technical debt reduction, and cost optimization, /li licoordinate external vendors and technology partners where required. /li /ul h3Your profile: /h3 ul li8+ years of experience in technical program management, product management, technical delivery, or a similar role, ideally involving cloud-based data platforms or scientific informatics systems, /li liproven experience leading large, cross-functional programs involving multiple engineering teams and business or scientific stakeholders, /li listrong background in life sciences, biopharma, biotech, or a closely related scientific domain, /li liability to communicate fluently with cell biologists, computational biologists, data scientists, and engineering teams, /li listrong understanding of human biological data and multi-omics data types, such as transcriptomics/RNA-seq, proteomics, and functional assays, /li lipractical knowledge of FAIR data principles, biological ontologies, metadata standards, and data governance, /li liexperience working in pharmaceutical or other highly regulated environments, with knowledge of GxP and/or 21 CFR Part 11, /li listrong technical background in software engineering, data engineering, technical architecture, or platform development, /li lisolid understanding of data pipelines, APIs, distributed systems, databases, and modern cloud platforms, /li lihands-on experience with GCP is required, including familiarity with services such as BigQuery, Workflows, Vertex AI, Cloud Run, and Google Cloud Storage, /li liexperience managing systems that ingest, process, store, and expose complex scientific or other large-scale datasets, /li liworking knowledge of SQL and NoSQL databases and modern data engineering practices, /li lifamiliarity with AI/ML platforms and MLOps concepts, /li listrong understanding of Agile, Scrum, and hybrid delivery models, /li liexpert knowledge of Jira and Confluence, with experience maintaining complex backlogs and requirements traceability, /li liexcellent stakeholder management, communication, facilitation, and conflict resolution skills, /li listrong analytical and strategic thinking, with the ability to navigate complex and ambiguous requirements, /li liexperience with high-performance computing (HPC), large-scale data processing, or HPC-to-cloud migration will be a plus, /li liknowledge of GCP architecture for large-scale scientific workloads and storage optimization will be a plus, /li liexperience with biological research workflows, in vitro cell models, high-throughput phenomics, or translational research will be a plus, /li liexperience with human data governance, patient privacy, data reproducibility, lineage, and audit readiness will be a plus, /li liexperience with vendor management and multi-vendor delivery environments will be a plus, /li lirelevant GCP certifications, such as Professional Cloud Architect or Professional Data Engineer, will be a plus. /li /ul /p #J-18808-Ljbffr