Technical Lead - Cloud Data Engineering - Snowflake / DBT

Your role:

Ready to shape the future? As Technical Lead Cloud Data Engineering, you own the technical direction of our Snowflake- and DBT-based data products from design to delivery. You are equally at home reviewing a data model, coaching a colleague, or presenting a design decision to senior management. You guide a cross-functional team, set engineering standards, and translate R&D business requirements into robust, scalable solutions – all while fostering a culture of quality, accountability, and continuous learning.

Your key responsibilities:

• Define end-to-end design of cloud data products; establish standards for data quality, security, GxP compliance, and CI/CD; document decisions as Design Decision Records (DDRs).
• Oversee implementation by internal and external engineers; provide expertise on Snowflake performance tuning, DBT pipeline design, SQL optimization, and Python-based processing.
• Mentor engineers at all levels; manage cross-team dependencies; communicate risks, trade-offs, and status clearly to all stakeholders.
• Scope and plan engineering work; balance feature delivery with technical debt; drive CI/CD adoption via Azure DevOps and automated data testing.
• Actively contribute to team growth through recruiting, onboarding, and knowledge sharing.

In return, we offer a high-impact role at the forefront of Healthcare R&D data innovation, a strong international engineering culture, flexible working models, and the purpose-driven environment of a global science and technology company.

Who you are:

Leadership & Mindset

• Accountable for team outcomes; leads by example and enables others to grow.
• Pragmatic: balances engineering excellence with real-world delivery constraints.
• Clear communicator across technical and non-technical audiences.

Experience & Qualifications

• Master's degree in Computer Science, Information Technology, or equivalent.
• 8+ years of hands-on data engineering experience, including significant technical lead responsibility.
• Deep expertise in Snowflake (architecture, performance tuning, data sharing) and DBT (pipeline design, testing, job automation).
• Strong proficiency in data modelling: Data Vault 2.0, OLAP/OLTP, and semantic ontologies.
• Advanced SQL and solid Python skills for data transformation and system integration.
• Proven CI/CD experience with Azure DevOps and Git; IaC with Terraform or CloudFormation is a plus.
• Familiarity with AWS data services (Glue, Step Functions, Athena, Lambda) is advantageous.
• Experience with GxP-compliant data products in a regulated (pharma/healthcare) environment is a strong plus.
• Business-fluent English (written and spoken)

Todos los candidatos internos, sin importar si trabajan a tiempo completo o parcial, tendrán la oportunidad de ser considerados para las vacantes disponibles

HC-HF-IRHE Engineering

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