Tech Lead Senior Architect Data Engineering

• 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