Senior Data Product Engineer, Enabling Functions 

At Genmab, we are dedicated to building extra[not]ordinary® futures, together, by developing antibody products and groundbreaking, knock-your-socks-off KYSO antibody medicines® that change lives and the future of cancer treatment and serious diseases. We strive to create, champion and maintain a global workplace where individuals' unique contributions are valued and drive innovative solutions to meet the needs of our patients, care partners, families and employees.

Our people are compassionate, candid, and purposeful, and our business is innovative and rooted in science. We believe that being proudly authentic and determined to be our best is essential to fulfilling our purpose. Yes, our work is incredibly serious and impactful, but we have big ambitions, bring a ton of care to pursuing them, and have a lot of fun while doing so.

Does this inspire you and feel like a fit? Then we would love to have you join us!

Role

We are looking for a Senior Data Product Engineer with deep expertise in DBT, Databricks, Power BI/Tableau and AWS, who can architect and implement scalable, reliable, and high-performance data products. This role will require strong technical skills across data modeling, distributed data processing, ELT pipeline development, and dashboarding, with an emphasis on automation, observability, and engineering best practices.

You will be expected to design and deliver production-grade data pipelines and models, optimize query, and compute performance, and expose data to end users through well-structured semantic layers and dashboards.

Responsibilities

Data Engineering & Architecture

• Architect and implement end-to-end ELT workflows with DBT (core and Cloud), ensuring modular, testable, and reusable transformations.

• Build high-performance data pipelines in Databricks (PySpark, Delta Lake, Unity Catalog) for batch and streaming workloads.

• Engineer scalable data ingestion pipelines into AWS (S3, Kinesis, Glue, Lambda, Step Functions) with strong monitoring and fault tolerance. Ensure observability, cost efficiency & scalability in all pipeline and compute designs.

• Design normalized and star-schema models for analytical workloads, following dbt's best practices and software engineering principles.

• Implement data quality testing frameworks (dbt tests, Great Expectations, or custom validations) with automated CI/CD integration.

• Manage data versioning, lineage, and governance through tools such as Unity Catalog and AWS Lake Formation.

• Develop semantic data layers that support self-service analytics across BI tools (Tableau, Power BI etc.).

• Build interactive, real-time dashboards with metric consistency and role-based access control.

• Partner with analysts and data scientists to optimize queries and deliver production-ready datasets.

• Automate deployment pipelines with CI/CD (GitHub Actions, GitLab CI, or AWS CodePipeline) for dbt and Databricks.

• Implement infrastructure-as-code (IaaC) for reproducibility (Terraform, CloudFormation).

• Ensure system reliability through observability and monitoring (Datadog, CloudWatch, Prometheus, or similar).

• Benchmark and optimize SQL, Spark, and BI query performance at scale.

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
• 8+ years in data engineering, analytics engineering, or data platform development.

• Expert-level proficiency in:

• DBT: advanced macros, Jinja, testing, exposures, dbt Cloud deployment.

• Databricks: Spark (PySpark, SQL), Delta Lake, Unity Catalog.

• AWS: S3, Glue, Lambda, Step Functions, Datasync, EMR, Redshift, IAM and networking/security fundamentals.

• Data Visualization: Power BI or Tableau.

• Strong programming background in Python and SQL (including query optimization).
• Proven experience with distributed systems and large-scale datasets (TB-PB scale).

• Experience implementing CI/CD pipelines, data testing, and infrastructure as code.

• Solid understanding of data governance, security, and compliance in enterprise environments.

• Experience with real-time data pipelines (Kafka, Kinesis, Delta Live Tables).

• Familiarity with containerization and orchestration (Docker, Kubernetes, EKS).

• Exposure to machine learning workflows in Databricks.

• 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

• You are genuinely passionate about our purpose
• You bring precision and excellence to all that you do
• You believe in our rooted-in-science approach to problem-solving
• You are a generous collaborator who can work in teams with a broad spectrum of backgrounds
• You take pride in enabling the best work of others on the team
• You can grapple with the unknown and be innovative
• You have experience working in a fast-growing, dynamic company (or a strong desire to)
• You work hard and are not afraid to have a little fun while you do so!