Software Engineering Senior Advisor- Hybrid

Cigna-Evernorth Services Inc. seeks a Software Engineering Senior Advisor for the Raleigh, NC location to design and build scalable data pipelines and ETL/ELT processes that can handle large amounts of both structured and unstructured data while ensuring security and reliability.

• Create and maintain data warehouse and data lake solutions using on-prem and cloud platforms like AWS.
• Design database structures and data models that perform well for analytical queries and reporting needs.
• Write clear technical documentation and specifications that explain how our data systems work.
• Research and recommend new data technologies and tools that can make our data infrastructure better and more efficient.
• Build, test, and deploy data pipelines using industry-standard tools such as Data Bricks, Airflow, Kafka, and similar technologies.
• Write and optimize SQL queries, stored procedures, and database components to extract and transform data efficiently.
• Create solutions that process data both in real-time and in batches.
• Set up automated checks to validate data quality and catch errors early in the pipeline.
• Connect and pull data from various sources including APIs, different databases, files, and streaming data platforms.
• Make data pipelines run faster and more cost‑effectively through optimization.
• Build frameworks and monitoring systems to ensure our data is accurate and trustworthy.
• Create and enforce data governance policies that set standards for how we handle and manage data.
• Implement security measures like encryption and access controls to protect sensitive data and ensure compliance with regulations such as GDPR, CCPA, or HIPAA.
• Perform data audits to find and fix any data integrity problems.
• Maintain documentation including data dictionaries, lineage tracking (showing where data comes from and where it goes), and metadata systems.
• Guide and mentor junior data engineers and analysts, helping them grow their skills.
• Review code written by team members to ensure quality and adherence to best practices.
• Lead discussions about technical design decisions and review proposed architectures.
• Work closely with software engineers and business analysts to understand what they need and deliver effective solutions.
• Monitor data systems to ensure they're running smoothly and fix issues when they arise.
• Find and eliminate performance bottlenecks that slow down data processing or storage.
• Set up monitoring and alert systems so we know immediately when something goes wrong with our data pipelines.
• Investigate the root causes of data incidents and put safeguards in place to prevent them from happening again.
• Manage cloud resources efficiently to keep costs under control while maintaining performance.
• Work with business stakeholders to understand their data needs and translate those needs into technical solutions.
• Provide technical advice and consultation to product managers and business leaders.
• Explain complex technical concepts in simple terms that non-technical team members can understand.
• Create clear documentation for technical processes, procedures, and system configurations so others can understand and maintain them.
• Hybrid work schedule.

• Bachelor’s degree in Computer Science, Electrical Engineering or related field and 5 years of experience in any software development role.
• Will accept a Master’s degree and 3 years of experience.
• Must have experience with:
  Hands‑on experience in designing, building, and optimizing end‑to‑end applications using Python, Java, PL/SQL, APIs, and frameworks;
• Software Development Life Cycle;
  Clean code practices;
  Debugging;
  Unit testing;
• Delivering scalable software;
  Modern data ecosystems including Data Lakes, Lakehouse, ELT/ETL pipelines, streaming, and batch processing;
• Building scalable data ingestion, transformation, orchestration, and optimization using cloud‑native services including AWS and Databricks;
• Tableau including building complex reports and hierarchical computations reports;
  Performance optimization;
  Report optimization;
  Writing a data pipeline using PySpark;
• Informatica Power Center components including source/target mapping, transformation, workflows, and…