Senior Data Engineer

If you’re eager to make a real impact in the health care industry through your own meaningful contributions, explore a role in technology with CVS Health. Our journey calls for technical innovators and data visionaries: come help us pave the way.

At CVS Health, we possess an extensive repository of healthcare data that spans over 150 million individuals, providing an unparalleled foundation for ambitious Data Engineers. In this role, you will engage with complex business challenges, harnessing modern tools and technologies to securely store, process, transform, and enrich terabyte to petabyte scale healthcare data. Your work will underpin data-driven business decisions and contribute to our mission of delivering industry-best data products / software with a customer-first mindset and team-oriented approach.

As a Senior Data Engineer, you will be instrumental in designing, developing, and maintaining optimal data pipelines to assemble large and intricate datasets, catering to the business requirements of various CVS lines of business. Collaborating closely with teams, you will craft tools to provide actionable insights and integrate them with consumer touchpoints.

In this role, you will:

• Develops large scale data structures and pipelines to organize, collect and standardize data that helps generate insights and addresses analytical needs.
• Collaborates with product business and data science team to collect user stories, translate into technical specifications, and implement data transformation, algorithms and models into automated processes.
• Builds highly scalable and extensible data marts and data models to support Data Science and other internal customers on Cloud. Integrates data from a variety of sources, assuring that they adhere to data quality and accessibility standards.
• Provide Guidance to a team of data engineers and collaborate closely with data scientists and analysts to support data-driven decision-making.
• Analyzes current information technology environments to identify and assess critical capabilities and recommend solutions.

As leaders in healthcare, our analytics and engineering teams deliver innovative solutions to business problems by collaborating with cross-functional teams in a dynamic and agile environment. You will be part of a team that values collaboration and encourages innovative thinking at all levels. You will be intellectually challenged to solve problems associated with large scale complex, structured and unstructured data, that will allow you to grow your technical skills and engineering expertise.

Required Qualifications:

• 3+ years of experience with SQL, NoSQL
• 3+ years of experience with Python (or a comparable scripting language)
• 3+ years of experience with Data warehouses (such as data modeling and technical architectures) and infrastructure components
• 3+ years of experience with ETL/ELT, and building high-volume data pipelines
• 3+ years of experience with reporting/analytic tools
• 3+ years of experience with Query optimization, data structures, transformation, metadata, dependency, and workload management
• 3+ years of experience with Big data and cloud architecture
• 3+ years of hands-on experience building modern data pipelines within a major cloud platform (GCP, AWS, Azure)
• 3+ years of experience with deployment/scaling of apps on containerized environment (i.e. Kubernetes, AKS)
• 3+ years of experience with real-time and streaming technology (i.e. Azure Event Hubs, Azure Functions, Kafka, Spark Streaming)
• 1+ year(s) of soliciting complex requirements and managing relationships with key stakeholders
• 1+ year(s) of experience independently managing deliverables

Preferred Qualifications:

• Experience in designing and building data engineering solutions in cloud environments (preferably GCP)
• 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
• Experience with complex systems and solving challenging analytical problems
• Strong collaboration and communication skills within and across teams
• Knowledge of data visualization and reporting
• Experience with schema design and dimensional data modeling
• Google Professional Data Engineer Certification
• Knowledge of microservices and SOA
• 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

Education:

Bachelor’s Degree or equivalent work experience in Computer Science, Information Systems, Data Engineering, Data Analytics, Machine Learning, or related field required. Master’s Degree preferred.