Data engineer in pharma

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• Lead the end-to-end architecture, design, and implementation of scalable data platforms using Snowflake.
• Define and enforce data architecture standards, including modeling, naming conventions, and best practices.
• Design and implement robust ETL/ELT pipelines using DBT and cloud-native tools.
• Collaborate with global stakeholders (business, analytics, clinical, and IT teams) to translate requirements into scalable solutions.
• Drive data governance, lineage, cataloging, and quality frameworks across the platform.
• Ensure compliance with European data regulations (e.g., GDPR) and pharma-specific standards.
• Implement CI/CD pipelines and DataOps practices for automated testing, deployment, and monitoring of data workflows.
• Optimize Snowflake performance, including query tuning, clustering, and cost management.
• Provide technical leadership, architectural guidance, and mentorship to engineering teams.
• Evaluate emerging tools and technologies to continuously improve the data ecosystem.
• Work closely with DevOps and infrastructure teams to ensure high availability, scalability, and security.

• 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).
• Будет плюсом: 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)

• Условий в вакансии нет