Software Engineering Senior Advisor- Hybrid

Cigna Group•Bloomfield, CT

5d•$163,821 - $173,600•Hybrid

About The Position

Cigna-Evernorth Services Inc. seeks a Software Engineering Senior Advisor in Bloomfield, Connecticut, to deliver software from requirements gathering through production deployment. The role works across system components, applying data engineering and big data methodologies to address business problems while prioritizing security, fault tolerance, scalability, quality, and automation. The position follows an iterative Agile approach and collaborates with engineering, product, and business teams. The role develops and supports data pipelines, data warehouses, ETL workflows, cloud-native architectures, and analytics solutions. It uses AWS services and data technologies to manage and process large volumes of structured and semi-structured data, support reporting and ad-hoc querying, and improve workflow performance. The position also implements CI/CD and deployment automation, maintains SQL databases, and provisions infrastructure through reusable Terraform modules. The position follows a hybrid work schedule. For occasional or permanent work from home, internet service must be cable broadband or fiber optic with speeds of at least 10 Mbps download and 5 Mbps upload. The posting lists a salary range of $163,821–$173,600 per year and separately anticipates a salary of $130,200–$217,000 per year, depending on relevant factors including experience and geographic location. The role is anticipated to be eligible for an annual bonus plan.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, or a related field.
Five years of experience in any software development role in the healthcare domain.
Experience designing, building, and supporting scalable data engineering and data warehousing solutions.
Experience with relational and analytical databases, including Teradata Vantage.
Experience with Databricks for scalable data engineering and analytic workloads.
Experience with cloud-based data platforms and AWS, including S3, Glue, Lambda, SNS, and CloudWatch.
Experience with cloud-native data architectures.
Experience with SQL, Python, and Spark for data transformation, automation, and analytics.
Experience with Apache Airflow for workflow orchestration, dependency management, and scheduling.
Experience with Informatica for enterprise-grade data integration and ETL processes.
Experience with IaaS and Terraform for data and application deployments using industry-standard automation tools.
Experience with CI/CD practices for data and application deployments using industry-standard automation tools.
Experience with GitHub and Jenkins.
Healthcare-domain knowledge, including membership, claims, and clinical data concepts.
Experience collaborating across engineering, product, and business teams to meet deadlines and quality expectations.

Responsibilities

Drive adoption of CI/CD tools and support improvements to toolsets and processes.
Create and deliver effective strategies and solution architectures to resolve issues.
Work across system components, using big data methodologies and application development to solve business problems while focusing on security, fault tolerance, and scalability.
Translate business objectives into technical specifications and work iteratively using Agile practices.
Write modular, referenceable code; design and architect solutions; and apply automation best practices.
Simplify processes and monitor data to identify and resolve issues before they affect the business.
Implement data pipelines, configure data, define table and column mappings, and create AWS buckets for file storage.
Configure bucket lifecycle policies to archive infrequently accessed data to appropriate storage classes.
Build data warehousing solutions for ad-hoc queries and analytics on large volumes of structured and semi-structured data.
Design and optimize queries for complex data transformations and aggregations supporting business intelligence and reporting.
Implement deployment automation using CI/CD tools.
Design and implement robust, scalable, high-performing end-to-end ETL pipelines.
Apply performance tuning, partitioning, and caching techniques to improve data-processing workflows.
Build event-driven architectures for asynchronous data processing.
Maintain SQL databases, create tables, views, and stored procedures, and optimize SQL queries.
Manage scalable, reusable Terraform modules for consistent resource provisioning across environments.
Collaborate across engineering, product, and business teams to meet deadlines and quality expectations.