Lead Data Architect @ Bayer
(práce v Polsku)

Lead Data Architect @ Bayer

Polsko

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.
• 8+ years of experience in data architecture or engineering.
• Expertise in data modeling, distributed systems, and cloud-native platforms.

Preferred Qualifications:

• Experience with big data technologies (e.g., Spark, Kafka, Snowflake).
• Strong understanding of data governance and compliance.
• Excellent cross-functional collaboration skills.

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.

For Digital Hub Warsaw, we are looking for:

Lead Data Architect

,[Lead the design, implementation, and governance of enterprise data architecture to support scalable, secure, and high-performance AI and analytics systems., Define and maintain enterprise-wide data architecture, including data models, schemas, metadata standards, and integration patterns., Establish data governance frameworks, including data quality, lineage, cataloging, and compliance., Lead modernization of data platforms, including cloud migration and distributed systems., Collaborate with AI Architects, Data Engineers, and ML Engineers to align infrastructure with AI workflows., Design for scalability, reliability, and performance across data systems., Evaluate and recommend tools, technologies, and best practices.] Requirements: Data modeling, cloud-native platforms, Big data, Spark, Kafka, Snowflake Additionally: Sport subscription, Training budget, Private healthcare, Company car, Canteen, Free parking, In-house trainings, Modern office.

Kategorie

data

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