Senior Data Engineering Architect 910 views

Job description

The Executive Advisor, Retail Pharmacy Personalization Data Engineering will lead a team of advanced data engineers to design, build, test, productionalize and support components of the Pharmacy Personalization engine. This role includes the data, feature, machine learning model, and business rule components of the analytics pipeline, the orchestration and productionalization of that pipeline, the structured experimentation in support of iterative testing and learning, and maintenance and enhancements of that pipeline over time to support an expanding set of Pharmacy personalization use cases. All of this is critical to driving pharmacy growth, and improving CVS patient adherence. This leader will collaborate with Data Scientists, Pharmacy business partners, and IT colleagues to accomplish the execution of the data and analytic roadmap for Pharmacy Personalization.

Position Summary: 

CVS is embarking on a multiyear journey to redefine the retail pharmacy experience for patients, in order to deliver a 1:1 personalized patient experience. To support this effort, a cross-functional Personalization Lab is being formed within the Pharmacy Growth and Innovation group. This Lab will be tasked with rapidly building, testing, and scaling high-priority use cases that drive incremental scripts and move the retail pharmacy business closer to the goal of a 1:1 personalized patient experience. These use cases require significant advances in the analytical models, supporting data structures, and data features leveraged to deliver patient interventions. As the Lead Data Engineer for the Pharmacy Personalization Lab, this leader will deploy teams to build the foundational analytics platform components required to support the long-term Personalization vision.

This leader will work closely with the Director, Data Strategy & Analytics, the Senior Director and the Vice President of Retail Pharmacy Personalization to design, build, productionalize and maintain the Personalization analytics pipeline, including data, features, models and business rule components required to execute the use cases. This leader will also work closely with the other Pharmacy and Information Technology colleagues to define the data and analytics roadmaps required to support the Personalization effort, and integrate those efforts together. They will also work closely with a variety of other data engineering experts from across the enterprise (e.g. Front Store, PBM) to leverage past learnings and share best practices.

Core Job responsibilities:

• Lead coding and architecting of end-to-end applications on modern data processing technology stack (e.g. Hadoop, Cloud, Spark ecosystem technologies)
• Drive collaborative reviews of design, code, data, features implementation performed by other data engineers in support of maintaining data engineering standards
• Build continuous integration/continuous delivery, test-driven development, and production deployment frameworks
• Troubleshoot complex data, features, personalization patient offer build rules issues and perform root cause analysis to proactively resolve product and operational issues (i.e., primary language python, L2-3 production support)
• Productionalize the full pipeline including distributed Machine Learning models (e.g., training/test pipeline, offer eligibility, data layer, feature layer, etc.)
• Connect business context and perspective to define model objective functions, features, business rules, prioritization, measurement, etc.
• Lead conversations with infrastructure teams (on-prem & cloud) on analytics application requirements (e.g., configuration, access, tools, services, compute capacity, etc.)
• Identify the skills and experience needed for Data Engineers, Machine Learning Engineers, and adjacent roles, and work with Personalization Lab leadership to make required hiring decisions as the Lab evolves over time.

Required Qualifications

• 3+ years leading data engineers and/or analytics-focused teams to deliver complex analytics projects on aggressive timelines
• 5+ years of Big Data, Machine Learning, and Spark experience building and running products and applications at scale, in production, in mission critical situations
• Full-time, 100% dedicated to Personalization Lab, ideally co-located with Lab in Customer Support Center.
• Platforms: Azure Cloud, DataBricks, Hadoop, Spark, Kafka, Kinesis, Oracle, TD
• Languages: PySpark, Python, Hive, Shell Scripting, SQL, Pig, Java / Scala
• Proficient in Map-Reduce, Spark, Airflow / Oozie / Jenkins, Hbase, Pig, No-SQL, Chef / Puppet, Git
• Familiarity with building data pipelines, data modeling, architecture & governance concepts
• Experience implementing ML models and building highly scalable and high availability systems
• Experience operating in distributed environments including cloud (Azure, GCP, AWS etc.)
• Experience building, launching and maintaining complex analytics pipelines in production

Preferred Qualifications

• Experience working via an agile, sprint-based working style
• Experience working side-by-side with business owners, and translating business needs into analytics solutions
• Proven ability to successfully balance near-term results (e.g., ability to design and execute on a ‘MVP’ model), with long-term goals
• Comfortable balancing quality of output with short timelines required to enable downstream functions

Education

• Bachelor’s degree in a field linked to data engineering, business analytics, applied mathematics, computer science, IT, computer applications, engineering or related field is required
• Advanced degree required in a field linked to business analytics, statistics, operations research, applied mathematics, computer science, engineering, or related fields