Data Engineer - Big Data Analytics Advisor

Job Description
Come be part of a dynamic team that is positioned at the apex of eliciting change in American’s health! As CVS Health now makes up a PBM (Caremark) and one of the nation’s largest health insurer (Aetna), you will have the opportunity to create programs that use an unprecedented level of health data to improve health outcomes. If you are passionate about making a difference in the work you do, being recognized for your talent and expertise in solving complex and challenging analytical/data problems while contributing to the success of key strategic initiatives, consider growing your career with a Fortune 10 healthcare leader!
As a Advisor for Data Engineering and Strategy specifically, in this role you will collaborate with PBM Product Advisors and Business partners and IT team, using the latest in data technology, you will be charged with:
• Making analytics faster, more insightful, and more efficient
• Building and maintaining a next-generation Analytics Data Layer for PBM Products
• Designing highly scalable and extensible data platform including but not limited to RDBMS / Big Data / Cloud which enables industrializing collection, storage, modeling, and analysis of massive data sets from heterogeneous channels
• Bringing a DevOps mindset to enable data and batch/real-time analytical solutions that leverage emerging technologies
• Developing prototypes and proof of concepts for the selected solutions, and implement complex data engineering projects
• Applying an analytic mindset to a focus on collecting, parsing, managing, and automating data feedback loops in support of business innovation
• Managing and addressing operational data issues by establishing workarounds and/or bringing in cross functional teams to solve the issues in timely manner

Required Qualifications
• 5 years of professional experience and business analytics experience including the following:
• Hands-on experience with “big data” platforms including Hadoop (preferably Azure or GCP) and Spark as well as experience with traditional RDBMS, preferably Teradata.
• Proficiency in “big data” technologies including Spark, Kafka, Hbase, Pig, NoSQL databases, etc
• Proficiency in one of the following programming languages: PySpark, Scala.
• Proficiency in following scripting languages: shell scripting, SQL and Teradata BTEQ
• Must be able to translate analytical problems into structured programs in PySpark or Scala
• Must have experience designing data models and solutions for analytical as well as reporting use cases

Preferred Qualifications
• Previous healthcare experience and domain knowledge
• Experience with cloud computing environment (ideally Microsoft Azure)
• Experience working on a large scale Spark implementation

Education
• B.S. Computer Science, Engineering, Statistics, Physics, Math or related fields.
• MS preferred – with coursework focused on advanced algorithms, mathematics in computing, data structures, etc.