Johnson Controls-posted 3 months ago
Full-time • Senior
Milwaukee, WI
Specialty Trade Contractors

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.

  • 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.
  • 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.
  • 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.
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