Senior Data Engineer: ETL & Analytics Pipelines

CVS Health; Arizona; Presencial; USD 83.000 - 222.000; Jornada completa

Descripción de la vacante

CVS Health is seeking a Sr. Data Engineer in Arizona to design and implement robust data pipelines powering analytics and data science workloads. You will model the Core Data Domain to support diverse access patterns and ensure scalable data infrastructure.

This hands-on role requires expertise in SQL, Python, and cloud platforms (Azure/AWS/GCP), with a focus on performance, governance, and collaboration with data scientists and analysts.

Formación

• 5+ years of applicable work experience.
• Strong SQL proficiency and ability to write complex queries.
• Experience in Python for ETL pipelines.
• Experience deploying data pipelines in cloud environments (Azure, AWS, GCP).
• Knowledge of data governance in cloud environments.
• Excellent communication and collaboration with data scientists, analysts, and product owners.

Responsabilidades

• Design data models and schemas to support analytics, reporting, and ML.
• Build ETL/ELT pipelines to ingest, process, and transform large datasets from multiple sources.
• Tune performance with partitioning and clustering to optimize queries and costs.
• Establish data quality standards and data governance policies for storage and access.
• Collaborate with data scientists and analysts to design data solutions that integrate with BI tools and ML models.
• Create comprehensive documentation for pipelines and processes and mentor junior engineers.
• Design and architect data infrastructure for analytical workloads and data marts.

Conocimientos

SQL

Python

ETL pipelines

Data modeling

Data governance

Communication

Cloud platforms

Educación

Bachelor's degree

Herramientas

Azure

AWS

GCP

Descripción del empleo

CVS Health is seeking a Sr. Data Engineer in Arizona to design and implement robust data pipelines powering analytics and data science workloads. You will model the Core Data Domain to support diverse access patterns and ensure scalable data infrastructure.

This hands-on role requires expertise in SQL, Python, and cloud platforms (Azure/AWS/GCP), with a focus on performance, governance, and collaboration with data scientists and analysts.