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Data Engineer
| Company | CVS Health |
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| Location | Richardson, TX, USA |
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| Salary | $72100 – $144200 |
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| Type | Full-Time |
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| Degrees | |
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| Experience Level | Junior |
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Requirements
- 1+ years of Experience in executing Data warehousing ETL projects.
- 1+ years of Experience with Python
- 1+ years of Experience with SQL
- 1+ years of experience with ETL/ELT, and building high-volume batch/realtime data pipelines
- 1+ years of hands-on Experience with bash shell scripts, UNIX utilities & UNIX Commands
- 1+ years of hands-on Experience with a major cloud platform (GCP, AWS, Azure)
Responsibilities
- Understand the Enterprise data systems and acquires knowledge on the relevant processes need for project delivery.
- Participate in project estimation process and provide inputs to Tech Lead.
- Participate in Agile scrum activities/project status meetings on regular basis.
- Participate in User story grooming/Design discussion with technical lead.
- Analyzes complex Data structure from disparate data sources and design large scale data engineering pipeline.
- Uses strong programming skills to build robust data pipelines for ETL (Extract / Transform / Load) processes, designs database systems and develops tools for data processing.
- Perform all Data Engineering job activities EDW/ETL project development/testing and deployment activities.
- Work closely with the developers on the ETL Jobs/Pipelines development.
- Create the Project process/automation by integrating the involved components.
- Documents data engineering processes, workflows, and systems for reference and knowledge-sharing purposes.
- Implements data quality checks and validation processes to ensure the accuracy, completeness, and consistency of the data.
- Be a team player and work with team members for Business solution and implementation.
Preferred Qualifications
- Experience with complex systems and solving challenging analytical problems
- Strong collaboration and communication skills within and across teams
- Knowledge of data visualization and reporting tools
- Implementation experience in building real time or near real time data pipelines using pub/sub or change data capture
- Knowledge on AI/ML model building using various libraries in Python along with data wrangling/data preparation experience
- Experience with Git, CI/CD pipeline, and other DevOps principles/best practices
- Experience with bash shell scripts, UNIX utilities & UNIX Commands
- Understanding of software development methodologies including waterfall and agile.
- Ability to leverage multiple tools and programming languages to analyze and manipulate data sets from disparate data sources
- Knowledge of API development, microservices and SOA
- Experience with schema design and dimensional data modeling
- Google Professional Data Engineer Certification
- Formal SAFe and/or agile experience. Previous healthcare experience and domain knowledge
- Experience designing, building, and maintaining data processing systems
- Experience architecting and building data warehouse and data lakes
