Infrastructure Engineering Senior Manager T500-11536
2 weeks ago
Position Summary:
The Enterprise Operations Analytics (EOA) organization supports the data and analytical needs of Cigna's Enterprise Operations.
As a center of excellence for best practices in Data Engineering, Web Application Development, Data Science, Advanced Analytics, and Business Intelligence, the team brings together data from customer contact centers, client benefit design/install, provider solutions / network operations, print / digital communications, and beyond in novel ways to provide actionable insights to business partners ranging from front-line Prior Authorization Representatives and Patient Care Advocates to Senior Leadership.
By turning data into information, and information into insight, we passionately strive to make the operational services provided by Cigna / Evernorth to customers, clients, and providers the safest, most efficient, most convenient, and most trusted in the world.
TheInfrastructure Engineering Senior Manager
will be a key contributor to ensure the successful delivery of ETL Services and Application Support.
To be successful in this role, you must have an advanced understanding of ETL processes and be experienced in supporting Production applications.
You must also have excellent communication skills and be able to build and maintain relationships with both internal and external stakeholders.
They will be responsible for partnering with key players in Customer Service, Client Service, Provider Service, and Workforce Planning, while drawing on support from Technology, Finance, Strategy, Operational Readiness, and Solutions Delivery.
Job Description & Responsibilities:
Responsible for design, development, deployment, and maintenance of Data Strategy solutions related to Cigna's Enterprise Operations.
Experience in developing PL/SQL code for data manipulation, validation, and reporting.
Performance Tuning and optimizing experience of SQL, PL/SQL code to reduce execution time or improve efficiency.
Design and develop data pipeline architectures using Databricks, Spark.
Collaborate with developers and DBAs to identify and implement solutions to improve system reliability and efficiency.
Provide first-line support for production issues, troubleshooting and resolving incidents in a timely manner.
Lead a team of advisors to direct work and prioritize the work pipeline.
Design, develop, and maintain data pipelines using Python ensuring scalability, reliability, and performance.
Experience Required:10+ years' experience in a Data Engineering role4+ years' experience in managing a team.
Experience Desired:
Ability to manage quickly changing priorities and in parallel maintain system continuity.
Experience in developing PL/SQL code for data manipulation, validation, and reporting.
Performance Tuning and optimizing experience of SQL, PL/SQL code to reduce execution time or improve efficiency.
Experience with scheduling tools such as CA Workload Automation.
Experience with Relational Database Development –
Oracle ,
Teradata ,
SQL Server , PostgreSQL or equivalent required.
Hands-on experience with AWS services, particularly in data storage, processing, and analytics.
Experience with Git and pull request workflow.
Education and Training Required:
Primary Skills:Hands-on experience in ETL Tools, SSIS, SQL Server, Oracle, Python, Databricks and SQL.
Additional Skills:
Should be a self-starter or can work independently.
Strong understanding of database concepts and experience with query optimization, performance tuning and cloud concepts.
Excellent troubleshooting and problem-solving skills, with the ability to analyze complex issues and implement effective solutions.
Strong communication and interpersonal skills, with the ability to work collaboratively in a fast-paced environment.
Work closely with cross-functional teams to troubleshoot and resolve production issues in a timely manner.
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