At CVS Health, the business problem is to transform health care by building a world of health around every consumer, and the Sr. Data Engineer (People Analytics) role is responsible for developing data warehouse modeling, data pipelines, and related analytics specific to People and Workforce analytics in cloud data platforms.
Requirements
- 5+ years' experience in Data Engineering, with a focus on HR or people data.
- 5+ years' experience with ETL/ELT processes and tools.
- 5+ years' experience with SQL and relational databases.
- 4+ years' experience programming in Python for data manipulation, automation, and analysis.
- 3+ years' experience with cloud platforms, prefer GCP (may consider Azure or AWS).
- 2+ years' experience with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).
- 2+ years' experience with scheduling tools like Airflow or Composer.
Responsibilities
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- Data Pipeline Management: Design, build, and manage robust data pipelines and ETL processes that integrate HR data from various systems, including Workday, talent management, payroll, and other data sources.
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- Data Engineering and Transformation: Develop and optimize data workflows to ensure data accuracy, quality, and availability for the People Analytics team and stakeholders across HR and business units.
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- Technical Leadership: Oversee a team of data engineers, providing mentorship, support, and guidance on best practices in data engineering, version control, and coding standards.
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- Analytics & Reporting Support: Work closely with People Analytics to structure data for analysis, develop data models, and create reproducible workflows that enable efficient reporting in R, Python, and other analytics tools.
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- Data Security and Compliance: Ensure data governance and security protocols are followed in accordance with company policies and industry regulations, with a focus on HR data confidentiality and compliance.
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- Collaboration with Stakeholders: Partner with HR leaders, IT, and People Analytics teams to understand business requirements, streamline data requests, and provide insights to support strategic decisions.
Other
- Bachelor’s degree in Computer Science, Data Engineering, Data Science, or a related field required.
- Master's degree preferred.
- Strong communication skills with the ability to communicate complex technical processes to non-technical stakeholders effectively.
- Problem-Solving ability and strong analytical skills with the ability to troubleshoot, optimize, and automate data processes.
- 40 hours per week, full-time
