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Tier-1 brand, hybrid/remote hiring, and a mid-level generalist data engineer title increase applicant competition.
Core data engineering skills are transferable, but People Analytics and HR system experience moderately limit cross-industry fit.
Explicit 5+ years plus mandatory Airflow, dbt, SQL, Python and AWS experience creates strict shortlisting filters.
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Architect and maintain scalable data infrastructure and ETL pipelines for people analytics within the People Experience organization.
Develop optimized data models and schemas to support workforce reporting and strategic decisions.
Implement data quality monitoring systems and collaborate with analysts and stakeholders to translate complex requirements into scalable data solutions.
Bachelor's degree in Computer Science, Information Systems, or related field, or equivalent practical experience.
Minimum 5 years of experience in data engineering roles.
Minimum 2 years of hands-on experience with Airflow and dbt for workflow orchestration and data transformation respectively.
Proficiency in SQL and Python; experience with AWS data services and cloud infrastructure.
Experienced in designing and maintaining data pipelines and infrastructure for HR/people analytics data environments.
Strong operational focus on data quality and reliable, scalable ETL workflows using modern tools (Airflow, dbt).
Comfortable partnering with analytics and business stakeholders to deliver actionable workforce data solutions.