Data Engineer - People Analytics

CVS Health•Washington, NV

1d•$83,430 - $222,480

About The Position

The Data Engineer - People Analytics is a technical developer and individual contributor on the People Analytics Data Engineering team. The role develops data warehouse models, data pipelines, and related analytics for People and Workforce analytics in cloud data platforms. It works with HR data and supports analysis and reporting for the People Analytics team and stakeholders across HR and business units.

Requirements

At least 3 years of experience in data engineering.
At least 3 years of experience with ETL/ELT processes and tools.
At least 3 years of experience with SQL and relational databases.
At least 2 years of experience programming in Python for data manipulation, automation, and analysis.
At least 3 years of experience with cloud platforms; GCP is preferred, though Azure or AWS may be considered.
At least 2 years of experience with data warehousing solutions such as Snowflake, Redshift, or BigQuery.
At least 2 years of experience with scheduling tools such as Airflow or Composer.
Bachelor’s degree in Computer Science, Data Engineering, Data Science, or a related field.

Nice To Haves

Experience with Workday or similar HRIS platforms and HR data flows.
Problem-solving ability and strong analytical skills, including troubleshooting, optimizing, and automating data processes.
Strong communication skills, including the ability to explain complex technical processes to non-technical stakeholders.
Familiarity or working knowledge of data visualization or business intelligence tools such as PowerBI, Tableau, Oracle BI, or Visier.
Technical experience in people or talent analytics, data engineering, visualization, business intelligence, or analytical consulting.
Master’s degree.

Responsibilities

Design, build, and manage data pipelines and ETL processes integrating HR data from Workday, talent management, payroll, and other systems.
Develop and optimize data workflows to support data accuracy, quality, and availability.
Oversee a team of data engineers, providing mentorship, support, and guidance on data engineering best practices, version control, and coding standards.
Work with People Analytics to structure data for analysis, develop data models, and create reproducible workflows for reporting in R, Python, and other analytics tools.
Ensure data governance and security protocols comply with company policies and industry regulations, particularly regarding HR data confidentiality.
Partner with HR leaders, IT, and People Analytics teams to understand business requirements, streamline data requests, and provide insights for strategic decisions.