Director, People Systems, Data Engineering & Architecture

Job Description

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