Director, People Systems, Data Engineering & Architecture

Role Summary

We are seeking a technically strong and strategically minded Head of People Systems Data Engineering & Architecture to lead the design, development, and governance of a modern HR data infrastructure. This leader will be responsible for the delivery of industry-leading data architecture and business intelligence engineering in support of HR decision science and reporting. This group will utilize cloud-based intelligent systems to collect, distribute, model, and analyze disparate and diverse data assets of all sizes to automate insights and drive business performance.

In addition, this role will play a critical part in laying the foundation for the responsible use of generative AI and large language models (LLMs), enabling advanced analytics, natural language interactions, and innovative AI-driven solutions that unlock new ways of working across HR.

You will build and lead a team of data engineers and collaborate closely with HRIS, IT, and the broader Workforce Analytics & Decision Science team to ensure that workforce data is clean, complete, and accessible - while meeting all privacy, compliance, and security standards.

Key Responsibilities

• Collaboratively design and execute business-focused strategies for BI infrastructure, data, and analytics - ensuring delivery of data driven solutions (Azure Data Factory / Databricks / SQL Database, Posit Connect).

• Establish the data and technical foundation to enable responsible use of large language models (LLMs) and generative AI, including data pipelines, model integration frameworks, and scalable infrastructure.

• Implement governance, security, and ethical AI practices to ensure responsible use of sensitive HR data in LLM and AI initiatives

• Partner closely with HR Ops, IT, cloud, and cybersecurity teams to align on infrastructure standards, ensure integration with corporate systems, and maintain a secure, resilient environment for HR data and AI initiatives.

• Design and maintain scalable, reliable ETL/ELT pipelines from critical ERP systems (e.g., Success Factors, Workday, LMS, ATS, survey tools (Qualtrics, Perceptyx, Glint).

• Maintain data integrity, lineage, and timeliness across core HR data domains (e.g., employee, org, performance, compensation, development)

• Work closely with People Analytics (AI/ML), Behavioral Science, and Systems Design teams to ensure the data infrastructure enables modeling, experimentation, and workflow integration

• Collaborate with the enterprise data engineering and HRIS teams to align tooling, schemas, and governance processes

• Provide technical guidance and partnership to HRBPs, COEs, and business leaders as needed

Required Qualifications

• STEM degree (Computer Science, Engineering, Information Systems/Management, or closely related field to analytics & Business Intelligence)

• 6+ years of experience in technologies and practice related to analytics/insights. Experience leading and working with cross-functional teams and communicating across organizations at all management levels

• Experience with analytical tools supporting data analysis, reporting and visualization (Tableau, Power BI, Shiny, Streamlit)

• Expertise in at least one programming language (Python, R)

• Experience with scripting and programming languages; SQL, Python/Scala and/or JAVA

• Experience working with cloud data platforms (e.g., Snowflake, Databricks, BigQuery, or Azure Synapse)

• Familiarity with HR systems like Workday, SuccessFactors, Greenhouse, or Cornerstone

• Deep understanding of data privacy, security, and governance practices

• Exposure to designing or supporting machine learning or generative AI solutions, with familiarity in large language model (LLM) frameworks and tools (e.g., Ollama, Hugging Face, OpenAI APIs, Azure OpenAI).

• Strong understanding of how to prepare, govern, and secure data for AI/ML applications, particularly when working with sensitive or regulated data such as HR data.

Preferred Qualifications

• Prior exposure to supporting data science or experimentation teams

• Understanding of ML Ops and real-time data pipelines

• Experience in HR data governance and management

• Ability to frame up, simplify, and translate complex problems, find root causes and hidden problems. Able to think holistically to understand the broader implications of a modern BI landscape

• Able to foster strong business relationships with partners across all enterprise functions

• Able to successfully influence and interact with partners at all levels

• Strong collaboration and communication (written & oral) skills