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Data Engineer
| Company | CVS Health |
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| Location | Smithfield, RI, USA |
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| Salary | $106038 – $150000 |
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| Type | Full-Time |
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| Degrees | Master’s |
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| Experience Level | Junior, Mid Level |
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Requirements
- Master’s degree (or foreign equivalent) in Computer Science, Data Science, Statistics, Mathematics, Analytics, Engineering, or a related field
- Two (2) years of experience in the job offered or related occupation
- Two (2) years of experience in Agile methodologies, or SAFe Software Development Principles
- Two (2) years of experience in REST, SOAP, or Web Service APIs
- Two (2) years of experience in data analytics on large data sets in healthcare, business, or retail sector
- Two (2) years of experience in JIRA, Rally or Confluence
- Two (2) years of experience in SAS or SQL programming languages
- Two (2) years of experience in writing application code and deploying to production
- Two (2) years of experience in Unix, Linux, or Shell scripting
- Two (2) years of experience in writing Extract/Transform/Load (ETL) processes
- Two (2) years of experience in managing large-scale data structures or ETL workflows
- Two (2) years of experience in data warehousing
- Two (2) years of experience in healthcare data management processes and techniques, including data standards, interoperability, and proper privacy data.
Responsibilities
- Develop large scale data structures and pipelines to organize, collect and standardize data to generate insights and address 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.
Preferred Qualifications
No preferred qualifications provided.
