Sr. Data Architect - Comm Analytics & AI

 

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

 

Sr. Data Architect - Comm Analytics & AI 

 

For Digital Hub Warsaw, we are looking for:


Sr. Data Architect –Commercial Analytics & AI

 

The Data & Analytics team at Bayer Consumer Health focuses on bringing digital transformation and innovation by creating best in class analytical solutions enabling data-driven decision making and performance optimization for Bayer Consumer Health organization.

You will be part of the data & analytics organization and are responsible to technically guide projects in the area of Pricing Analytics. You partner with business stakeholders, data scientists, analytics leads as well as implementation partners/vendors and are the leading data architect for our analytical products. You ensure a proper data management, data ingestion and data pipeline orchestration and that a scalable and well performing analytical product is build. If you are interested in joining a young and dynamic team driving the digital transformation of Bayer Consumer Health, we would like to hear from you.

 

Key Tasks & Responsibilities:
 

• Collaborate with business functions (global customer excellence team & country net revenue managers & marketing teams) and other IT colleagues such as core data asset architects, data scientists, Full stack engineers and analytics leads and cloud architects/engineers) to ensure proper project execution.
• Lead technical implementation of analytic and AI solutions in the area of Pricing and Commercial Analytics. Ensure developers or providers follow our best practices and design principles as a solid foundation in order to deliver fit-for purpose & scalable analytical & AI products.
• Assess data requirements of the analytics solution and collaborate with core data asset architects to bring needed data to our platform, jointly define needed data quality checks and data management processes.
• Lead the integration of different data sources (e.g. trade promotion data, pricing data, sell-out data, sell-in data etc.) and the design of the data models needed as input for AI applications or data marts meeting the business requirements
• Define architecture of AI solutions/applications, by collecting and assessing functional and non-functional requirements and translate them into technical concepts considering user needs, robustness, scalability, re-usability, cost efficiency, performance & security & data privacy requirements.
• Lead the implementation of proper dev/ops processes
• Collaborate closely with the platform team to continuously enhance the data and AI technology stack of our global cloud-based data, analytics and AI platform.
• Together with the product owner of the solution steer external providers or internal developers, guide them as architect, provide cost and time estimations, challenge vendor costs and assure quality delivery of vendor implementations & proper handover to support.

 

Qualifications & Competencies (education, skills, experience):
 

• Master degree in Computer Science, Engineering, or similar

• 5+ years' working experience in the field of Data & Analytics and AI, preferably in the area of pricing, M&S & CPG industry
• Proficient knowhow in data engineering and data architecture including common data management techniques using following tech stack: Azure Data Lake/Blob, Databricks, Python, especially PySpark & SQL. BI/reporting solutions like Tableau or PowerBi as well as Snowflake are a plus.
• Profound data content knowledge (sell-out and pos data, sell-in data, pricing and Trade promotion data) and M&S process knowhow
• Good understanding or application architectu