Requirements

Expected technologies

Azure

Databricks

Unity Catalogue

Collibra

Power BI

SQL

Python

Our requirements

• Master's or PhD degree with 8+ years of experience in data management, data analytics, data engineering, data architecture, data science or related fields.
• Experience with developing and delivering data products within modern tech stack, particularly Azure, Databricks, Unity Catalogue, Collibra and Power BI.
• Strong understanding of data modelling, ETL processes, data governance platforms, data quality tools & methodologies, metadata management, SQL, Python and Agentic AI concept.
• Extensive experience in leading cross-functional teams and managing complex data strategy, governance and quality initiatives in enterprise environments.
• Deep understanding of data governance frameworks, data stewardship principles, master & meta data management, data privacy regulations, licensed data contracts and regulatory compliance requirements.
• Ability to design and implement comprehensive data quality frameworks, data lineage tracking, and automated monitoring systems.
• Strong analytical and problem-solving skills with keen attention to detail and ability to translate business requirements into technical data solutions.
• Excellent interpersonal, communication and collaboration skills, with proven ability to engage and influence stakeholders at all organizational levels, from technical teams to C-suite executives.
• Experience with agile methodologies, project management, and change management in data transformation initiatives.
• Fluent in English, both written and spoken.
• Ability to travel.

Your responsibilities

• Develop and implement a comprehensive data strategy to prepare data assets for easy consumption by business stakeholders, internal IT teams, autonomous AI systems, and data professionals, while drastically decreasing time to market for data science and business intelligence initiatives through improved data availability, quality, and semantics.
• Lead and coordinate core data asset teams (market, consumer, customer, product, company, environmental, and master data management), including data analysts, data stewards, data governors, data architects, and data engineers, to optimize data assets for maximum usability and business value, while maintaining a focus on cost-effectiveness.
• Establish and enforce data governance frameworks, policies, and standards to ensure data quality, completness, consistency, semantics, documentation, security, compliance, and regulatory adherence.
• Actively identify, evaluate, and prioritize new data sources and datasets, determining their strategic value and integration feasibility into the data asset portfolio.
• Foster collaboration across cross-functional teams to promote data governance best practices, driving a culture of data stewardship and accountability throughout the organization.
• Participate in strategic data initiatives and exploratory projects that investigate emerging data management technologies, keeping Bayer at the forefront of data asset optimization in the consumer health sector.
• Create and execute Data Assets, Analytics and AI Platform’s strategic vision as part of the Platform’s Leadership Team.