People Technology Data Engineer

This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Join the People Technology Team at Adyen At Adyen, we believe people are our greatest asset and we want to ensure we deliver the best employee experience globally. People Technology is evolving rapidly from a traditional HRIS function into a high-leverage Product & Engineering Engine. As part of our Build HR Technology & Analytics team, we are looking for a People Technology Data Engineer based out of our Amsterdam office. In this role, you will lead the data engineering and analytics infrastructure layer for our People organization. You will design, build, and maintain high-performance data pipelines, scalable data models, and automated transformations that ingest employee data from Workday and satellite systems into our central enterprise big-data platform. Your mission is to make People data reliable, scalable, governed, and consumable for People Analytics, workforce planning, executive reporting, and downstream AI applications. Key Responsibilities • Build & scale People data pipelines: Design, develop, and maintain high-volume ETL/ELT pipelines to extract, transform, and ingest data from Workday (via RaaS/WQL/APIs) and other People platforms into our central enterprise data warehouse. • Architect People data models & data marts: Create clean, scalable data models, schemas, and data marts optimized for People Analytics, executive dashboards, workforce modeling, and programmatic consumers. • Ensure data quality, lineage & performance: Implement automated data quality checks, testing frameworks (e.g., dbt test, Great Expectations), anomaly detection, and end-to-end lineage tracking across all People data workflows. • Embed security, privacy & data governance: Enforce strict data governance, fine-grained access controls, automated data masking, and retention rules across sensitive employee data (PII) in compliance with global privacy standards (GDPR/CCPA). • Power analytics & AI use cases: Turn raw transactional data into reusable data products and API endpoints that feed BI dashboards, predictive workforce analytics, and generative AI features (e.g., Gemini Enterprise). • Partner across Data & Analytics: Collaborate closely with People Analysts, Enterprise Data Engineering, Applications Engineers, and Security teams to align on data governance and eliminate manual data extracts. Qualifications • Data Engineering Expertise: 5+ years of hands-on data engineering experience building complex ETL/ELT pipelines, data warehouses, and data models in an international environment. • Core Technical Stack: Advanced proficiency in SQL and Python for data transformation, workflow orchestration (e.g., Airflow/Dagster), transformation frameworks (e.g., dbt), and cloud data platforms (Snowflake/BigQuery). • Software Engineering & CI/CD: Experience applying software engineering best practices to data development, including version control (Git), automated testing, and CI/CD pipelines for data workflows. • HRIS Data & API Foundations: Demonstrated experience extracting and modeling HR data from Workday using RaaS reports, WQL, REST/SOAP APIs, and custom REST endpoints/webhooks. • Data Observability & Testi