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At CVS Health, we’re building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care. As the nation’s leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose-driven colleagues – caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate. And we do it all with heart, each and every day.
Job Responsibility:
Develop large scale data structures and pipelines to organize, collect and standardize data to generate insights and addresses reporting needs
Write ETL (Extract/Transform/Load) 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
Requirements:
Master’s degree (or foreign equivalent) in Computer Science, Engineering, Data Science, Statistics, Mathematics, Analytics, or a related field and two (2) years of experience in the job offered or related occupation
Data analysis for retail and/or healthcare industries
Programming in Java, Python, or R
SAS or SQL programming languages
Databases: Oracle, Teradata, or DB2
Spark, PySpark, or Scala
Marketing analytics, clinical trials, or health research
Designing data models and solutions for analytical and reporting use cases
Writing Extract/Transform/Load (ETL) processes
Cloud technologies: Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP)
Quantitative analysis techniques, including data pipelines, distributed computing engines, and machine learning infrastructure design
What we offer:
Full range of medical, dental, and vision benefits
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