Design and implement data platform solutions integrating Airflow, Databricks, DBT, Django and Reltio within a cloud-based data platform (AWS preferred).
Leverage Unity Catalog as a metastore, Delta Lake, and the medallion architecture to establish scalable and well-governed data solutions.
Integrate the data platform with compute, AI and other analytical systems including facilitation of varying MLOps solutions in collaboration with the AI platform team
Contribute to cohesiveness of Genmab’s broader data ecosystem, including third-party tools, external data sources, and integrations with partner organizations.
Guide the implementation and optimization of scalable, efficient data pipelines, workflows, and data mesh implementations.
Develop components of the data marketplace including aspects of full-stack development.
Define best practices, architectural frameworks, and standards for modern cloud-based data platforms in a regulated environment.
Collaborate with data governance teams to translate governance policies into technical solutions, ensuring data quality, lineage tracking, access control, and compliance.
Identify reusable solution patterns that reduce governance friction and accelerate compliant data usage across business functions
Engage with data producers, consumers, stewards, and data engineers to tailor solutions that fit their needs.
Ensure GxP compliance, regulatory adherence, and best practices in data security for all data workflows.
Requirements
Bachelor’s degree in Computer Science, Bioinformatics, or a related field is required.
Master’s or Ph.D. in a relevant field is a plus.
10+ years of experience in data engineering, data architecture, or related roles.
Expertise in Airflow, Databricks (2 -3 years experience), DBT, and Reltio, with a strong understanding of orchestration, transformation, and master data management (MDM) in biotech.
Familiarity and ability to deliver components of a data marketplace in a hands-on format, which includes components of full-stack development.
Understanding of AI and analytics and how data needs to be leveraged to facilitate model development
Proficiency in Python, with experience developing scalable data pipelines and cloud-based (Databricks) architectures.
Strong knowledge of GxP and regulatory compliance in biotech/pharma data platforms preferred.
Experience designing and implementing data mesh architectures and data marketplaces.
Proven ability to work with data governance teams to ensure alignment with enterprise metadata management, lineage tracking, and access control.
Excellent stakeholder management, communication, and influencing skills across technical and non-technical teams.
Biotech or pharma experience preferred, with a deep understanding of how data flows across R&D (e.g., translational research, bioinformatics), CMC (e.g., batch records, stability data), and Commercial (e.g., omnichannel engagement, sales ops) contexts in biotech/pharma.
Ability to balance hands-on technical work with technical leadership.
Exposure to modern data lakehouse architectures leveraging Delta Lake, medallion architecture, and Unity Catalog is a plus.
Benefits
401(k) Plan: 100% match on the first 6% of contributions
Health Benefits: Two medical plan options (including HDHP with HSA), dental, and vision insurance
Voluntary Plans: Critical illness, accident, and hospital indemnity insurance
Time Off: Paid vacation, sick leave, holidays, and 12 weeks of discretionary paid parental leave
Support Resources: Access to child and adult backup care, family support programs, financial wellness tools, and emotional well-being support
Additional Perks: Commuter benefits, tuition reimbursement, and a Lifestyle Spending Account for wellness and personal expenses
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