Lead Data Engineer (People Analytics, Hybrid)

Job summary

This position involves building and maintaining a robust data foundation on the Databricks platform to support the People, Places & Culture organization in making data-driven decisions. The role focuses on developing scalable data solutions that enhance the reliability and accessibility of people data.

Qualifications

• Background in data engineering, analytics, or a related field.
• Strong SQL skills and proficiency in Python.
• Understanding of dimensional data warehouse modeling concepts.
• Experience or interest in modern data platform technologies like Databricks or Spark.
• Continuous improvement mindset with a focus on optimizing workflows.
• Interest in machine learning and AI capabilities.

Responsibilities

• Design and implement dimensional data warehouse models to ensure high data reliability and quality.
• Develop automated data pipelines using SQL and Python to minimize manual reporting efforts.
• Implement data quality checks and monitoring processes for trusted data pipelines.
• Provide data and tools to the People, Places & Culture organization to enhance strategic priorities.
• Build a well-structured data infrastructure to support future analytics capabilities.

Skills

• Proficiency in SQL and Python for data pipeline development.
• Familiarity with data governance principles and APIs.
• Experience with visualization tools like Power BI is a plus.
• Understanding of CI/CD practices for managing data workflows.

Education

• Relevant degree in data engineering, analytics, or a related field preferred.

Tools

• Databricks, SQL, Python, Power BI, GitHub, and familiarity with HCM systems like Workday or SuccessFactors is advantageous.