Tech Lead / Senior Architect - Data Engineering w Polska

• Strong hands-on expertise in Snowflake (data warehousing, performance tuning, security, cost optimization).
• Deep understanding of data warehousing concepts (dimensional modeling, star/snowflake schemas).
• Advanced proficiency in SQL and complex query optimization.
• Extensive experience in ETL/ELT development, especially with DBT.
• Experience in data architecture and distributed data systems design.
• Strong exposure to CI/CD pipelines (Git, Jenkins, GitHub Actions, Azure DevOps).
• Experience working with cloud platforms (AWS).

Preferred Skills:

• ​ Experience with orchestration tools like Apache Airflow or similar.
• Exposure to data lake / lakehouse architectures.
• Experience with data visualization tools (Tableau, Power BI).
• Prior experience in pharmaceutical / healthcare domain (clinical, R&D, or commercial data).

Leadership & Soft Skills

• Strong stakeholder management and communication skills across business and technical teams.
• Ability to drive architecture decisions and influence enterprise data strategy.
• Experience working in Agile/Scrum environments

We are seeking a highly experienced Tech Lead / Senior Architect – Data Engineering to drive the end-to-end design and implementation of enterprise-grade data platforms for a major global engagement within the pharmaceutical and life sciences sector .

In this role, you will be instrumental in architecting scalable, highly secure, and compliant data solutions that empower advanced analytics, clinical trial insights, and enterprise-wide business intelligence to support data-driven healthcare innovations.

,[Platform Architecture & Delivery: Lead the end-to-end architecture, design, and implementation of scalable, high-performance data platforms built on Snowflake., Standards & Best Practices: Define, establish, and enforce enterprise data architecture standards, including dimensional/data modeling, naming conventions, design patterns, and engineering best practices., Modern Pipelines & ETL/ELT: Design and implement robust, maintainable ETL/ELT pipelines leveraging dbt (data build tool) alongside modern cloud-native technologies., Global Stakeholder Engagement: Collaborate closely with distributed cross-functional stakeholders—including business leaders, data scientists, clinical domain experts, and IT teams—translating complex business requirements into robust, scalable technical architectures., Data Governance & Quality: Champion and implement comprehensive data governance, data lineage, metadata management, cataloging, and automated data quality frameworks across the ecosystem., Regulatory Compliance & Security: Ensure data platforms rigorously comply with European data protection regulations (e.g., GDPR) as well as pharma-specific compliance, validation, and security guidelines., DataOps & Automation: Implement modern DataOps methodologies and robust CI/CD pipelines for automated testing, deployment, workflow orchestration, and active platform monitoring., Snowflake Optimization: Oversee advanced Snowflake performance tuning, query optimization, clustering strategies, storage tiering, and cloud cost management (FinOps)., Technical Leadership & Mentorship: Provide strategic architectural guidance, code reviews, and hands-on mentorship to empower and upskill engineering teams., Continuous Innovation: Continuously evaluate emerging technologies, data frameworks, and modern tools to evolve and optimize the data platform landscape., Cross-functional Collaboration: Partner closely with Cloud Infrastructure, SecOps, and DevOps teams to guarantee platform high availability ] Requirements: SQL, Snowflake, ETL, AWS, CI/CD, Data, Apache Airflow, Data Lake, Tableau, Power BI, Data warehouse, Git, Jenkins, GitHub