Sr Data Engineer

CVS Health•Irving, TX

4d•$114,379 - $185,400•Remote

About The Position

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Caremark LLC, a CVS Health company, is hiring for the following role in Irving, TX: Sr Data Engineer to develop, build and manage large-scale data structures, pipelines and efficient Extract/Load/Transform (ETL) workflows to address complex problems and support business applications.

Requirements

Master’s degree (or foreign equivalent) in Computational Science, Data Science, Statistics, Mathematics, Analytics, or a related field.
Completion of a graduate-level course, research project, internship, or thesis in CI/CD, Jenkins, and GIT.
Completion of a graduate-level course, research project, internship, or thesis in Python.
Completion of a graduate-level course, research project, internship, or thesis in Agile methodologies or SAFe Software Development Principles.
Completion of a graduate-level course, research project, internship, or thesis in Docker or Kubernetes.
Completion of a graduate-level course, research project, internship, or thesis in JIRA, Rally, or Confluence.
Completion of a graduate-level course, research project, internship, or thesis in Amazon Web Services (AWS).
Completion of a graduate-level course, research project, internship, or thesis in Machine learning, statistical analysis, and predictive modeling.
Completion of a graduate-level course, research project, internship, or thesis in Feature engineering, modeling training, hyperparameter tuning, distributed model training, and supervised and unsupervised learning implementation.
Completion of a graduate-level course, research project, internship, or thesis in Quantitative analysis techniques, including clustering, regression, and pattern recognition.

Responsibilities

Develop large scale data structures and pipelines to organize, collect and standardize data to generate insights and addresses reporting needs.
Write ETL (Extract, Load, Transform) processes, design database systems, and develop tools for real-time and offline analytic processing that improve existing systems and expand capabilities.
Collaborate with Data Science team to transform data and integrate algorithms and models into automated processes.
Test and maintain systems and troubleshoot malfunctions.
Leverage knowledge of Hadoop architecture, HDFS commands, and designing and optimizing queries to build data pipelines.
Utilize programming skills in Python, Java, or similar languages to build robust data pipelines and dynamic systems.
Build data marts and data models to support Data Science and other internal customers.
Integrate data from a variety of sources and ensure adherence to data quality and accessibility standards.
Analyze current information technology environments to identify and assess critical capabilities and recommend solutions to complex business problems.
Experiment with available tools and advise on new tools to provide optimal solutions that meet the requirements dictated by the model/use case.