Lead Data Architect - Product Supply

The Data Assets, Analytics & AI team at Bayer Consumer Health focuses on digital transformation and innovation by creating analytical solutions for data-driven decision making and performance optimization. The role is part of this organization, responsible for technically guiding projects related to core data assets and commercial analytics, partnering with data architects, business stakeholders, data scientists, and vendors to build scalable analytical products.

• Bachelor/Master degree in Computer Science, Engineering, or similar.
• 8+ years experience in data-related areas, 5+ years in Data & Analytics, preferably in Product Supply & CPG industry.
• Excellent knowledge in data architecture, technology, data engineering, and data management (e.g., data quality).
• Expertise in Azure Databricks, ADF, Azure Container Services, AzureML, Azure Foundry.
• Programming skills in SQL, experience with SQL/NoSQL databases, PySpark (DataFrame API, Spark SQL, MLlib), pandas, SQLAlchemy, parallel processing, advanced data transformation, and performance optimization.
• Experience with BI/reporting tools like PowerBi/Tableau.
• Knowledge of application development frameworks (Django, Flask, FastAPI) and JavaScript UI frameworks (React.js, Next.js) is a plus.
• Profound business and data knowledge in product supply domain (product data, formulations, quality data, orders, procurement, finance data such as COGS).
• Experience steering implementation teams of internal and external engineers.
• Strong problem-solving, analytical skills, and business judgment.
• Interpersonal, communication, active listening, consulting, challenging, presentation skills.
• Fluent English (written and spoken).
• Intercultural awareness (Europe, US, India) and willingness to travel occasionally.

• Lead technical implementation of analytic projects in Product Supply, ensuring adherence to best practices and design principles for scalable data products.
• Design, lead, and manage integration of various data sources and design reusable data models/marts to meet business requirements and AI architecture.
• Contribute to data management creation and steer implementation of data management processes with core data asset architects.
• Initiate and prepare Architecture Change Advisory Boards; collaborate with data architects, business functions, analytics leads, data science teams, and platform architects.
• Collaborate with global and regional business stakeholders and IT teams to ensure delivery aligns with business priorities and IT objectives.
• As technical lead, steer external providers and internal teams, provide cost/time estimations, challenge vendor costs, assure quality delivery, and proper handover.
• Contribute to enrichment of cloud-based data & analytics technology stacks according to analytics product needs.