Data Engineer — People Analytics & HR Data Pipelines

Quest Oracle Community; Providence (RI); On-site; USD 83,000 - 222,000; Full time

Job summary

CVS Health is seeking a Data Engineer - People Analytics to design and build data pipelines, models, and analytics for HR/workforce insights in cloud platforms.

You will integrate Workday and payroll data, ensure data quality and security, and enable reproducible reporting in Python and R through collaboration with HR and IT. This role supports data-driven decision making across the organization.

Qualifications

• 3+ years' experience in Data Engineering.
• 3+ years' experience with ETL/ELT processes and tools.
• 3+ years' experience with SQL and relational databases.
• 2+ years' experience programming in Python for data manipulation, automation, and analysis.
• 3+ years' experience with cloud platforms (GCP preferred).
• 2+ years' experience with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).
• 2+ years' experience with scheduling tools like Airflow or Composer.

Responsibilities

• Design, build, and manage data pipelines and ETL processes for HR data.
• Develop and optimize data workflows for accuracy and availability.
• Oversee a team of data engineers and promote best practices.
• Collaborate with HR analytics to structure data for analysis and reporting.
• Ensure data governance and security in line with policies and regulations.
• Partner with HR, IT, and stakeholders to deliver insights and requirements.

Skills

Data Engineering

ETL/ELT

SQL & relational databases

Python for data manipulation

Cloud platforms (GCP preferred)

Data warehousing (Snowflake/Redshift/\

Scheduling tools (Airflow/Composer)

Education

Bachelor's degree in CS / Data Eng / Data Science

Master's degree preferred

Tools

Workday

PowerBI

Tableau

Oracle BI

Visier

Job description

CVS Health is seeking a Data Engineer - People Analytics to design and build data pipelines, models, and analytics for HR/workforce insights in cloud platforms.

You will integrate Workday and payroll data, ensure data quality and security, and enable reproducible reporting in Python and R through collaboration with HR and IT. This role supports data-driven decision making across the organization.