Data Engineer

Position Summary A Data Engineer will develop, build, and manage large-scale data structures, pipelines, and efficient ETL workflows to address complex problems and support business applications. 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. Requirements Master’s degree (or foreign equivalent) in Computer Science, Data Science, Statistics, Mathematics, Analytics, or a related field. Completion of a university-level course, research project, internship, or thesis in each of the following topics: CI/CD, Jenkins, GIT, or DevOps Programming in Java, Python, and R SAS or SQL programming languages Agile methodologies or SAFe Software Development Principles Spark, PySpark, and Scala Hadoop architecture or HDFS commands MySQL and NoSQL Visualization tools: PowerBI and Tableau Designing and optimizing queries to build data pipelines Machine learning, statistical analysis, and predictive modeling NLP (Scikit, SpaCity, Pytorch, or Spark NLP) Vertex-AI PyData ecosystem Writing Extract/Transform/Load (ETL) processes Designing data architectures, including data pipelines, distributed computing engines, and machine learning infrastructure design Developing and deploying predictive models or ML systems in a cloud environment (GCP, AWS, or Azure) Compensation Pay Range: $142,418.00/year to $158,620.00/year. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above and includes an award target in the company’s equity award program. Benefits A full range of medical, dental, and vision benefits. Eligible employees may enroll in the Company’s 401(k) retirement savings plan, and an Employee Stock Purchase Plan is also available for eligible employees. The Company provides a fully-paid term life insurance plan to eligible employees, as well as short-term and long-term disability benefits. CVS Health also offers numerous well-being programs, education assistance, free development courses, a CVS store discount, and discount programs with participating partners. Employees enjoy Paid Time Off (“PTO”) or vacation pay, paid holidays throughout the calendar year, and sick time and other time off consistent with relevant state law and Company policies. Equal Employment Opportunity Statement Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws. #J-18808-Ljbffr