People Analytics Data Engineer

JOB PURPOSE

To design, develop, and maintain scalable HR data pipelines, data models, and analytical data infrastructure that enable reliable People Analytics and data-driven HR decision-making. The role is responsible for integrating data from multiple HR systems, ensuring data quality and consistency, and providing trusted datasets for dashboards, reporting, and advanced analytics.

KEY ACCOUNTABILITIES

• Design, develop, and maintain ETL/ELT pipelines to integrate HR data from multiple sources such as HRIS, payroll, attendance, recruitment, performance, survey, and other HR systems.
• Develop and maintain HR Data Warehouse structures, including fact tables, dimension tables, and historical employee datasets.
• Build and maintain analytical data models and semantic layers to support People Analytics dashboards, reports, and self-service analytics.
• Ensure data accuracy, consistency, completeness, and reliability across HR data sources and analytical platforms.
• Develop automated data validation, reconciliation, and data quality monitoring processes.
• Optimize SQL queries, ETL processes, data models, and data refresh performance to ensure scalable and efficient analytical solutions.
• Integrate structured and semi-structured data from databases, APIs, files, and other internal systems into the People Analytics data platform.
• Implement and maintain appropriate data access, security, and governance mechanisms for sensitive employee and HR data.
• Collaborate with HR functions, IT, and system owners to translate business requirements into reliable data solutions.
• Document data models, data pipelines, business rules, data lineage, and technical specifications to support maintainability and data governance.
• Support the development of advanced analytics, automation, and AI-driven People Analytics solutions by providing reliable and well-structured data foundations.

QUALIFICATIONS

• Bachelor's degree in Computer Engineering, Information Technology, Computer Science, Industrial Engineering, Data Science, or a related field.
• 2+ years of experience in Data Engineering, Business Intelligence, Data Warehousing, or a related data role.
• Strong proficiency in SQL and relational database concepts.
• Hands-on experience in designing and developing ETL/ELT processes.
• Good understanding of Data Warehouse concepts, dimensional modeling, fact/dimension design, and historical data management.
• Experience with Microsoft SQL Server and related data technologies is required.
• Familiarity with analytical/semantic data models and BI platforms such as Power BI and SSAS Tabular is required.
• Experience with Python for data processing, automation, or data integration is preferred.
• Experience working with APIs, MySQL, files, or multiple data sources is an advantage.
• Understanding of data quality, data governance, data security, and access management concepts.
• Familiarity with HR data or People Analytics concepts is an advantage but not mandatory.