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Lead Data Solutions Architect

Roche
5 days ago
Full-time
Remote friendly (Warsaw, Masovian Voivodeship, Poland)
Poland
228,900 zł - 425,100 zł PLN yearly
Solutions Architect

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections,  where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

The Position

Lead Data Solutions Architect

Roche Digital Technology (RDT) is where innovation meets purpose. As a global team at the heart of Roche, we are a community of business-minded technologists committed to help shape tomorrow’s digital future of healthcare. Our mission is to power Roche through cutting-edge digital technologies, harnessing the potential of artificial intelligence, data, and scalable tech innovations. Driven by purpose and passion, we’re building a future where digital is a core strength across all of Roche, enabling smarter ways of working, unlocking human potential, and driving breakthroughs that truly matter for millions of patients around the world.

At Roche, we offer a hybrid work model that combines flexibility with in-person collaboration. For now, we require our employees to be in our offices on average two days per week. The specific office days may vary depending on business needs, such as workshops, conferences, town halls, team meetings, and other collaborative events.

This role is embedded within our core Diagnostics division, where we bridge scientific curiosity with technical excellence to build a decentralized, enterprise-wide data ecosystem. As a technical cornerstone, you will act as the bridge between global technology and local business, working side-by-side with Data Domain Leads and Product Owners to transform raw data into trustworthy data products. Joining our team offers a unique opportunity to shape a sustainable, data-driven future that accelerates life-changing solutions for patients worldwide.

The opportunity:

  • Architectural Leadership: Drive the overarching design of Data Mesh architectures and integrated data solutions from source identification to the final data product, ensuring full lifecycle alignment with business needs.

  • Data Product Delivery & Governance: Lead the definition and implementation of reusable, discoverable, and well-governed Data Products while ensuring strict compliance with access management, data classification, audit traceability, and regulatory standards (e.g., GxP, GDPR).

  • Cross-Functional Collaboration: Partner dynamically with Data Domain Leads, Sub-Domain Leads, and Data Product Owners to translate complex business requirements into robust, scalable data architecture proposals.

  • Team Leadership & Technical Mentorship: Direct and mentor a dedicated delivery team of external data engineers, elevating technical standards and fostering a culture of ownership and continuous improvement.

  • Technology & Pipeline Optimization: Innovate and optimize domain data processes, focusing on pipeline design and enterprise data modeling strategies to meet system and user requirements.

  • Modern Data Stack Execution: Oversee end-to-end data pipeline buildout and cloud performance optimization using Python, dbt, GitLab CI/CD, Talend, and API consumption.

Who you are:

  • Data Architecture & Mesh Mastery (Required): Proven track record of designing and implementing Data Mesh architectures, managing cloud platforms like Snowflake (AWS is an advantage), and managing Data Products in complex enterprise environments.

  • Advanced Data Modeling & Ingestion (Required): Deep hands-on experience designing scalable enterprise data models utilizing Data Vault 2.0 methodology and dimensional modeling, paired with expertise in Python, dbt, GitLab CI/CD, Talend, and API ingestion.

  • Data Quality & Observability Focus (Required): Extensive experience applying data quality standards across entire data pipelines, with strong familiarity with observability principles to ensure system health.

  • Stakeholder Engagement