Staff Data Engineer - Scalable Pipelines & AI Tools

9025 CVS Shared Services Resources LLC

Illinois

Hybrid

USD 107,000 - 261,000

Full time

2 days ago
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Benefits offered by this job

Benefits package

Job summary

CVS Health is seeking a senior data engineer to design and develop large-scale data structures and ETL pipelines. You will standardize data sources, enable real-time and offline analytics, and deploy analytics programs for predictive modeling.

You will collaborate with executives, product and design teams to address data-related needs and mentor junior engineers. The role emphasizes data reliability, efficiency, and quality while leveraging cloud platforms (GCP/AWS/Azure) and GenAI capabilities.

Qualifications

  • 7–10 years work experience in data engineering or related field.
  • Bachelor's degree or equivalent in CS/Engineering/ML or related discipline.
  • Adept at problem solving and decision making.
  • Adept at collaboration and teamwork.
  • Adept at growth mindset and continuous learning.
  • Adept at execution and delivering solutions.
  • Adept at business intelligence.

Responsibilities

  • Design and develop complex data structures and pipelines to organize, collect and standardize data.
  • Build ETL processes and data architectures for real-time and offline analytics.
  • Collaborate with executives, product and design teams to address data needs.
  • Coach junior team members and share knowledge across the company.

Skills

Problem solving
Collaboration
Growth mindset
Execution
Business intelligence

Education

Bachelor's degree in Computer Science, Engineering, ML or related

Tools

GCP
Azure
AWS
GenAI

Job description

CVS Health is seeking a senior data engineer to design and develop large-scale data structures and ETL pipelines. You will standardize data sources, enable real-time and offline analytics, and deploy analytics programs for predictive modeling.

You will collaborate with executives, product and design teams to address data-related needs and mentor junior engineers. The role emphasizes data reliability, efficiency, and quality while leveraging cloud platforms (GCP/AWS/Azure) and GenAI capabilities.

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