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Data Engineer
| Company | CVS Health |
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| Location | Irving, TX, USA |
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| Salary | $122949 – $180000 |
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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, Information Technology, Computer Information Systems, Engineering, or a related field
- one (1) year of experience in the job offered or a related occupation
- one (1) year of experience with machine learning operations, including model versioning, model and data lineage, and model deployment, scalability and orchestration
- one (1) year of experience with designing data models and solutions for analytical and reporting use cases
- one (1) year of experience with CI/CD, Jenkins, GIT, or DevOps
- one (1) year of experience with programming in Python, R, or SQL
- one (1) year of experience with Spark, Airflow, Kafka, Hbase, Pig, MySQL, or NoSQL
- one (1) year of experience with Oracle, Teradata, or DB2
- one (1) year of experience with quantitative analysis techniques, including clustering, regression, and pattern recognition
- one (1) year of experience with software development lifecycle (SDLC)
- one (1) year of experience contributing to largescale applications development, data science, or data analytics projects
- one (1) year of experience designing data architectures, including data pipelines, distributed computing engines, and machine learning infrastructure design
- one (1) year of experience with data analytics on large data sets in healthcare, business, or retail sector
- one (1) year of experience with healthcare data management processes and techniques, including data standards, interoperability, and data privacy
- one (1) year of experience with cloud components including cluster management
Responsibilities
- Analyze data engineering problems and develop, build and manage large-scale data structures, pipelines and efficient Extract/Load/Transform (ETL) workflows
- 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.
