Data Architecture and Platform Ownership

• Define and evolve the data architecture for pharma commercial analytics across ingestion, storage, transformation, semantics, and consumption layers
• Operate Redshift, SnapLogic, Power BI, and Python runtimes for reliability, performance, and cost; align with IT on security, networking, and identity
• Set and enforce standards for modeling (star schema, medallion), metadata, lineage, data quality, and access controls in line with regulations and AZ policies

Data Engineering and Data Products

• Build and run production ETL/ELT pipelines integrating first- and third-party sources (SAP, Salesforce/Veeva, CRM/CLM, digital, email/web, syndicated, formulary/market access, field activity)
• Deliver reusable, well-documented data products and curated datasets optimized for Power BI, with SLAs, monitoring, and incident management
• Orchestrate dataflows and CI/CD; manage demand and releases via Azure DevOps/JIRA/GitHub

Power BI Reporting and Decision Enablement

• Lead enterprise Power BI datasets, DAX measures, and certified dashboards for commercial performance, brands, field effectiveness, omnichannel, and market dynamics
• Govern KPIs, RLS/segmentation, usage monitoring, versioning, and lifecycle to drive trust and adoption
• Partner with Commercial Excellence, Digital Customer Engagement, brand teams, and broader stakeholders to turn requirements into actionable visual narratives

Advanced Analytics & AI (incl. ML)

• Apply practical data science techniques, such as regression, clustering/segmentation, time series, and NLP to augment BI with predictive and diagnostic insight where appropriate, using Python (and optionally R)
• Operationalize models within the governed environment with traceability, quality monitoring, and business interpretability

Collaboration and Impact

• Bridge business (sales, marketing, market access, insights) and IT/platform teams to align priorities, ensure data readiness, and deliver high-value use cases
• Champion data literacy and self-service; mentor contributors and coordinate external partners in a matrix setup
• Track impact with platform and adoption KPIs (pipeline reliability/latency, data quality, dashboard usage, time-to-insight, business outcome proxies), * A trusted, compliant data foundation with reliable pipelines, high data quality, and performant semantic models
• High-adoption Power BI dashboards that provide consistent, timely insights for commercial decision-making
• Accelerated delivery of data products and analytics use cases, measured by reduced time-to-insight and demonstrated business impact
• Clear governance and operating model for data demand, releases, and lifecycle management

We offer

When we put unexpected teams in the same room, we fuel ambitious thinking with the power to encourage life-changing medicines. In-person working gives us the platform we need to connect, work at pace, and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office.

But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Do you have experience in SQL?, Do you have a Master's degree?, * 5+ years of experience spanning data engineering and business intelligence, with hands-on ownership of data platforms, pipelines, and enterprise reporting in a regulated or complex environment; pharmaceutical or life sciences exposure is advantageous

• Bachelor's degree (Master's preferred) in Computer Science, Data/Software Engineering, Statistics, Mathematics, Health Informatics, or related discipline
• Expert SQL and strong Python; experience with data modeling (star schema, medallion), semantic layer design, and performance tuning
• Proven delivery of at least two end-to-end data warehouse/BI/visualisation initiatives, from ingestion through production reporting
• Proficiency operating cloud data services and DevOps practices (e.g., Redshift, SnapLogic, Power BI, Python runtimes; Informatica/Databricks a plus)
• Familiarity with commercial pharma datasets and systems (e.g., SAP, Salesforce, Veeva CRM/Align, digital engagement and web analytics, email marketing platforms)
• Practical understanding of advanced analytics and statistical programming; ability to apply ML/NLP thoughtfully to commercial problems
• Strong communication and stakeholder management skills, with the ability to convey complex concepts to nontechnical audiences and drive alignment in a matrix environment
• Fluent in English; German or French is a plus