As a Senior People Analytics Data Engineer, you will play a crucial role in owning workforce data transformation and modeling within the modern cloud data stack. Your primary responsibility will be to build scalable and reusable workforce data models that convert HR and business data into reliable and structured datasets. By partnering closely with People leaders, you will standardize core workforce metrics and enhance long-term data trust across dashboards and reporting layers. This role reports to the Head of People Analytics and operates independently within a global SaaS environment, focusing on scalable transformation and modeling rather than infrastructure engineering or predictive data science. **Key Responsibilities:**
Own the end-to-end design and integrity of workforce data models, including dimensional structures, grain definition, and SCD logic. - Build and optimize transformation frameworks using dbt and advanced SQL within the cloud data warehouse. - Standardize and govern core People metrics to ensure consistent definitions across dashboards and reporting layers. - Translate business requirements into scalable and reusable data models. - Implement and maintain testing, validation, and documentation practices to strengthen long-term data trust. - Proactively resolve metric inconsistencies and reduce reporting conflicts. - Partner directly with senior People stakeholders to drive clarity and alignment in workforce reporting. **Qualifications Required:**
7+ years of experience in Analytics Engineering, Data Modeling, or related data roles. - Bachelor's degree in computer science, Information Systems, Data Science, Statistics, or a related quantitative field. - Strong expertise in advanced SQL, including window functions, complex joins, CTE structure, and performance optimization. - Hands-on experience with dbt and building scalable transformation layers. - Deep knowledge of dimensional modeling, including fact/dimension design and SCD logic. - Experience working in a cloud data warehouse environment (Snowflake preferred; BigQuery or Redshift acceptable). - Understanding of core People metrics such as headcount, attrition, workforce movement, compensation, and diversity. - Comfortable partnering with senior stakeholders to translate business needs into structured data solutions. - Experience leveraging AI capabilities within cloud data platforms to enhance workflow transformation and metric reliability. - Familiarity with People Analytics or HR Analytics environments, and knowledge of Workday reporting or HCM data integration is beneficial. Please note that AI is embedded in workflows and decision-making within this role. Successful candidates are expected to embrace AI as an essential capability, apply AI technologies to business challenges, and stay curious about new trends and best practices related to AI. As a Senior People Analytics Data Engineer, you will play a crucial role in owning workforce data transformation and modeling within the modern cloud data stack. Your primary responsibility will be to build scalable and reusable workforce data models that convert HR and business data into reliable and structured datasets. By partnering closely with People leaders, you will standardize core workforce metrics and enhance long-term data trust across dashboards and reporting layers. This role reports to the Head of People Analytics and operates independently within a global SaaS environment, focusing on scalable transformation and modeling rather than infrastructure engineering or predictive data science. **Key Responsibilities:**
Own the end-to-end design and integrity of workforce data models, including dimensional structures, grain definition, and SCD logic. - Build and optimize transformation frameworks using dbt and advanced SQL within the cloud data warehouse. - Standardize and govern core People metrics to ensure consistent definitions across dashboards and reporting layers. - Translate business requirements into scalable and reusable data models. - Implement and maintain testing, validation, and documentation practices to strengthen long-term data trust. - Proactively resolve metric inconsistencies and reduce reporting conflicts. - Partner directly with senior People stakeholders to drive clarity and alignment in workforce reporting. **Qualifications Required:**
7+ years of experience in Analytics Engineering, Data Modeling, or related data roles. - Bachelor's degree in computer science, Information Systems, Data Science, Statistics, or a related quantitative field. - Strong expertise in advanced SQL, including window functions, complex joins, CTE structure, and performance optimization. - Hands-on experience with dbt and building scalable transformation layers. - Deep knowledge of dimensional modeling, including fact/dimension design and SCD logic. - Experience working in a cloud data warehouse environment (Snowflake preferred; BigQuery or Redshift acceptable). - Understand