Senior Data Engineer - Global People Data

As Senior Data Engineer, you will lead the design and delivery of enterprise-grade data pipelines and models that power workforce analytics and regulatory reporting for a global 100K+ employee population. You will own canonical data structures and enforce standards across a multi-source data landscape, partnering with cross-functional teams to align with the broader data platform. This is a hands-on role with full technical autonomy, shaping scalable, governance-driven data assets. You’ll contribute to strategic people analytics that inform reporting and compliance at scale.

• Lead design and implementation of core data pipelines ingesting data from multiple HR systems (including Workday) into an enterprise data model using Databricks and Delta Lake
• Own and evolve canonical people data structures and enforce schemas, ingestion patterns, and transformation logic for scalability and governance
• Make day-to-day architectural and design decisions independently to accelerate delivery
• Ensure pipelines support regulatory reporting and compliance (EU Pay Transparency Directive, UK Gender Pay Gap, ESG/CSRD)
• Collaborate with enterprise data and business platform teams to align with data platform standards and integration patterns
• Provide senior technical guidance, code reviews, and architectural oversight to other data engineers
• Embed data quality checks, validation frameworks, and governance controls for audit-ready analytics and reporting
• Operate in a lean, fast-moving, globally distributed environment with autonomy

• Hands-on data engineering experience designing and delivering complex pipelines and data models in a cloud environment
• Proficiency in SQL; solid Python and/or PySpark capability
• Experience with Databricks, Apache Spark, and Delta Lake architecture
• Ability to design and own enterprise-grade canonical data models across multiple upstream sources
• Experience integrating data from APIs and diverse upstream platforms at scale
• Azure cloud platform experience
• Strong data governance mindset with validation, reconciliation, and audit framework development
• Ability to make independent technical design decisions and guide others

• collaboration
• autonomy
• problem-solving
• SQL
• Python
• PySpark