Descripción de la oferta
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 & QualificationsMaster'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 disponiblesHC-HF-IRHE EngineeringRL Expert 3
