Application Development Senior Advisor- Hybrid

Cigna Healthcare•Morris Plains, NJ

1d•$122,200 - $203,600•Hybrid

About The Position

Cigna-Evernorth Services Inc. is hiring an Application Development Senior Advisor in Morris Plains, New Jersey, to develop real-time and batch-processing data pipelines that enhance Cigna’s digital experiences and analytics. The role involves building production-grade data solutions and machine-learning workflows, contributing to architectural decisions, and ensuring that data solutions meet business requirements and quality and performance standards. The position also advances data governance and security in the healthcare domain, including generating and cataloging metadata, configuring privacy controls for personally identifiable and protected health information, and implementing row-level security. It leads adoption of generative-AI-assisted development practices and prompt engineering, and manages GitHub repositories and CI/CD pipelines for deploying Databricks jobs and notebooks. The advisor works with executive, product, and engineering stakeholders to resolve technical data issues and support infrastructure needs, while mentoring junior engineers and helping translate business requirements into scalable data solutions. The schedule is hybrid. The role is anticipated to be eligible for an annual bonus plan.

Requirements

Master’s degree in Computer Science, Business Analytics, or a related field and 3 years of experience, or a bachelor’s degree and 5 years of experience.
Experience developing and managing scalable ETL pipelines, collaborative analytics workflows, and production-grade data solutions using PySpark.
Experience leveraging AWS S3 for storage and integration.
Experience writing advanced SQL queries for data extraction, transformation, and analysis in large-scale data environments.
Experience designing and implementing logical and physical data models.
Experience applying schema-design best practices.
Experience maintaining enterprise-level data warehouses with reliable ETL processes.
Experience orchestrating, monitoring, and optimizing big-data pipelines for ingestion, transformation, and quality assurance of high-volume data across distributed computing frameworks.
Experience troubleshooting and optimizing query performance, execution plans, and resource allocation for large-scale datasets.

Responsibilities

Develop solutions using AWS, Databricks, Airflow, Redshift, DynamoDB, Elasticsearch, RDS, Snowflake, and machine-learning tools.
Develop production data pipelines using Spark with Scala, Python, and SQL, and implement machine-learning algorithms on Databricks and AWS.
Participate in architectural decision-making for data pipelines and implement advanced analytics solutions aligned with organizational goals.
Assemble large and complex data sets to meet functional and analytics business requirements while maintaining high quality and performance standards.
Use generative AI tools to create descriptions for data tables and columns and ingest the generated metadata into the Collibra Data Catalog through APIs.
Implement data governance and access controls in the healthcare domain.
Configure Immuta for column-level masking of PII and PHI and for row-level security.
Lead adoption of generative-AI-enhanced development pipelines using Cursor AI for debugging, code generation, and context-aware engineering across multi-file projects.
Apply and iteratively refine prompt-engineering techniques to improve the reliability and performance of AI-driven data workflows.
Manage GitHub repositories and GitHub Actions CI/CD pipelines to automate deployment of Databricks jobs and notebooks.
Collaborate with executive leadership, product, and engineering stakeholders to resolve data-related technical issues and support data infrastructure needs.
Mentor and upskill junior engineers, and help translate complex business requirements into scalable data solutions.