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.
Define end-to-end design of cloud data products; establish standards for data quality, security, GxP compliance, and CI/CD; provide expertise on Snowflake performance tuning, DBT pipeline design, SQL optimization, and Python-based processing.
Scope and plan engineering work; drive CI/CD adoption via Azure DevOps and automated data testing.
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 general science and technology company.
Pragmatic:
balances engineering excellence with real-world delivery constraints.
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
📌 Technical Lead (España)
🏢 Merck
📍 España