Sr. Manager, Data Engineering

CVS Health•Irving, TX

1d•$119,330 - $236,900•Hybrid

About The Position

Caremark LLC., a CVS Health company, is hiring for the following role in Irving, TX: Sr. Manager, Data Engineering to plan, initiate, and manage information technology (IT) projects for data engineering and analytics. Duties include: work with business and technical partners from across the enterprise to support the development of innovative programs to improve patient outcomes, reduce cost, and improve efficiency across the organization; manage project execution to ensure adherence to budget, schedule, and scope, and assess business implications; enable data-driven strategic decision-making and identify opportunities for existing product improvement and new product development; translate business needs into analytic questions and utilize Python, SAS, and SQL to access data and develop Tableau dashboards to track milestones and deliverables; design and conduct rigorous analyses of pharmacy claims, medical claims, and other data, and translate analytical findings for business and customer audiences; responsible for data stewardship, including improving the quality and usage of data and ensuring high levels of data quality in enterprise data warehouse and source systems; analyze, evaluate, and test the integration of multiple data sources into the data warehouse and remedy data deficiencies in warehouse environments; utilize data modeling concepts to collaborate with member of the Business, Operations, and IT teams to understand requirements, research data anomalies, and ensure consistency and quality; test newly developed functionality to ensure the highest level of data quality upon delivery; and mentor junior team members. Telecommuting available. Multiple positions.

Requirements

Bachelor’s degree (or foreign equivalent) in Computer Science, Computer Engineering, Information Technology, Engineering, or a related field and five (5) years of progressive, postbaccalaureate experience in the job offered or related occupation.
Software development lifecycle (SDLC)
CI/CD, Jenkins, GIT, or DevOps
Docker and Kubernetes
JIRA, Rally, or Confluence
PowerBI or Tableau
XML, JSON, HTML, CSS, or JavaScript
Cloud technologies: Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP)
Dataflow, Big Query, and DataFlow
Pivotal Cloud Foundry (PCF)
Splunk, DynaTrace, AppDynamics, Grafana, or Prometheus
Preparing high level design document (HLD) and proof of concept (POC) for new implementations
Extract/Transform/Load (ETL) processes to extract data from disparate source transaction systems, transform and enrich the data, and load it into specific data models optimized for analysis and reporting.

Responsibilities

Plan, initiate, and manage information technology (IT) projects for data engineering and analytics.
Work with business and technical partners from across the enterprise to support the development of innovative programs to improve patient outcomes, reduce cost, and improve efficiency across the organization.
Manage project execution to ensure adherence to budget, schedule, and scope, and assess business implications.
Enable data-driven strategic decision-making and identify opportunities for existing product improvement and new product development.
Translate business needs into analytic questions and utilize Python, SAS, and SQL to access data and develop Tableau dashboards to track milestones and deliverables.
Design and conduct rigorous analyses of pharmacy claims, medical claims, and other data, and translate analytical findings for business and customer audiences.
Responsible for data stewardship, including improving the quality and usage of data and ensuring high levels of data quality in enterprise data warehouse and source systems.
Analyze, evaluate, and test the integration of multiple data sources into the data warehouse and remedy data deficiencies in warehouse environments.
Utilize data modeling concepts to collaborate with members of the Business, Operations, and IT teams to understand requirements, research data anomalies, and ensure consistency and quality.
Test newly developed functionality to ensure the highest level of data quality upon delivery.
Mentor junior team members.