About this role
This is a remote position.
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.
Key Responsibilities:
- 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 (HA), resilience, and top-tier security standards.
Requirements
- 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