Software Engineering Advisor- Hybrid

Cigna-Evernorth Services Inc. seeks a Software Engineering Advisor for the Bloomfield, CT location to design, build, and optimize scalable batch and streaming data pipelines using Python, SQL, and Spark (Databricks/EMR), ensuring reliability, performance, and maintainability.

Responsibilities:

- Develop and support Teradata Vantage solutions leveraging Query Grid/ Clear Scape Analytics/ AI Unlimited for advanced analytics, feature engineering, and high-performance SQL workloads.

- Implement cloud-native data platforms on AWS (S3, Glue, EC2, VPC, IAM, Lake Formation), including secure networking, role-based access, and governed data lake patterns.

- Build and manage lakehouse storage using Delta Lake plus open table formats (Apache Iceberg/Hudi), enabling ACID transactions, schema evolution, time travel, and efficient incremental processing.

- Provision and standardize infrastructure using Terraform, delivering repeatable environments and enforcing best practices for configuration, tagging, cost controls, and security.

- Create and operate CI/CD pipelines and Dev Ops automation (Git, Cloud Bees/ Jenkins, Ansible), including code quality gates, automated testing, and release orchestration.

- Integrate governance and privacy controls using tools like Immuta and Delphix, including policy enforcement, dynamic masking, tokenization, and compliant environment refresh processes.

- Design observability and incident response workflows with Splunk (logs/ metrics/ alerts), enabling proactive monitoring, root-cause analysis, and improved operational SLAs.

- Enable analytics and self-service reporting by publishing curated datasets and semantic layers for BI tools (Tableau/Looker), ensuring consistent KPI definitions and data quality.

- Apply prompt engineering and AWS Bedrock capabilities to prototype and product ionize GenAI-enabled data/automation use cases, following SDLC standards, security controls, and responsible AI practices.

- Hybrid work schedule.

Qualifications:

- Bachelor's degree in Computer Science, Computer Engineering or related field and 5 years of experience in any software engineering role in the healthcare domain.

- Must have experience with:
Designing and building large scale data pipelines using Python and Apache Spark (Databricks);
Teradata;

- supporting both batch and scheduled processing including data validation and quality checks;

- AWS data and computational services to deploy, secure, and monitor production data workloads including S3, Glue, EC2, IAM, VPC, Lake Formation, and Cloudwatch;

- Developing reusable Python libraries and frameworks for automation, ETL utilities, DDL validation, and test data validation, with adoption across multiple engineering teams;

- Implementation and ownership of CI/CD pipelines using Jenkins and Cloud Bees including automated testing, quality gates, versioning, and controlled release workflows; working with Teradata Vantage (QG/OTF/TD MCP);

- Oracle including performance aware query design and schema validation;
Modern data lake technologies for reliable and scalable data storage including Delta Lake, Apache Iceburg, and Apache Hudi;

- Design and implementation of REST APIs including contract definition, input validation, backwards compatibility, and secure access patterns;
Kafka experience including developing and operating producer/ consumer for data ingestion and integration workflows;

- Data protection and compliance implementation, including data masking and tokenization using tools such as Delphix, particularly for lower environment refreshes from production;
Infrastructure automation using Terraform, enabling repeatable, compliant environment provisioning;

- End to end SDLC ownership in an Agile/Scrum environment including requirements analysis, solution design, code reviews, unit and integration testing, and production support;

- Incorporating AI features into data or automation solutions in an enterprise environment including using cursor, Copilot/VSCode, and MCP servers;
Development and orchestration of data workflows including scheduling, dependency management, and failure handling;

- Automation of operational and reporting workflows, including building data pipelines and BI dashboards to reduce manual reporting using Looker and Tableau;

- Scripting and automation background including using Python, Groovy, and Shell to eliminate repetitive operational tasks; and, working in regulated enterprise environments with awareness of data privacy, security, and audit requirements.

Salary…