Lead Data Engineer (Cross Domain) - dsm-firmenich

Overview

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In this Lead Data Engineer role, you will own end-to-end data pipelines across Bronze, Silver and Gold layers, enabling scalable data products for the Procurement domain. You will drive DevOps-centric deployment practices in Azure DevOps and GitHub, collaborating with modelers, stewards, and business partners to deliver production-grade solutions. You’ll work with dbt, Databricks, PySpark, and CI/CD automation to shape data architecture and governance at scale. This position offers leadership opportunities, cross-functional impact, and exposure to cutting-edge data engineering practices in a global setting.

Compensaciones / Beneficios

• growth opportunities
• global teamwork
• culture of collaboration
• learning and development
• voice and influence in shaping future
• opportunity to impact millions

Responsabilidades

• Design and implement end-to-end data pipelines for ingestion, transformation, and storage across Bronze, Silver, and Gold layers
• Develop and manage data ingestion processes from source systems via ETL and API-based methods
• Build modular transformation frameworks using dbt, PySpark, and SQL with staging models and load metadata in alignment with Data Vault 2.0
• Design, build, and maintain CI/CD and DevOps processes in Azure DevOps and GitHub Actions with automated testing and governance
• Implement IaC and deployment automation for data platform resources (dbt, Databricks, clusters, dependencies)
• Establish monitoring, observability, and operational excellence for pipeline reliability and rapid issue resolution
• Drive data quality, governance, and compliance with automated testing, lineage, and FAIR data principles
• Provide technical leadership and cross-functional collaboration across data engineers, modelers, stewards, BI developers, data scientists, and business SMEs

Requisitos principales

• Strong technical expertise in dbt, SQL, Python, Spark (PySpark), Databricks, Git, Azure DevOps, and GitHub
• Proven experience designing and maintaining production-grade data pipelines (5+ years)
• Deep CI/CD and automation experience with Azure DevOps Pipelines and GitHub Actions; xqbhyrx IaC knowledge (Terraform, Bicep) is a plus
• Advanced Git and repository management; governance across Azure DevOps and GitHub
• Cloud data engineering experience (Azure) with Databricks jobs, clusters, and workflows
• Extensive knowledge of Data Vault 2.0 architecture (Raw Vault, Business Vault, Gold-layer models)
• Experience with data ingestion patterns (batch ETL, incremental, CDC, API-based ingestion)
• Strong focus on data governance and quality; exposure to scientific datasets is a plus
• Leadership mindset with ability to lead teams, manage projects, and collaborate across functions and geographies

• leadership
• collaboration
• curiosity
• dbt
• SQL
• Python