Sr. Data Engineer (51249)

Index Analytics is seeking a Data Engineer to support Government clients to design, build, and optimize scalable data pipelines and cloud-based solutions. The Data Engineer plays a key role in modernizing the organization’s data ecosystem by helping transition legacy data analytics solutions to a contemporary infrastructure. This role blends advanced data engineering with hands‑on cloud solutions engineering, leveraging AWS, Snowflake, and modern DevOps practices. The ideal candidate has experience delivering high‑quality solutions in an Agile environment.

The customer is very mission-focused, technically knowledgeable, and provides excellent support. This is an attractive and stimulating role on an amazing program that aims to make a real difference. The analytics system developed by the team at Index directly supports investigators, auditors, and other analysts working to identify and deter fraud, reduce waste, curtail patient harm, protect vulnerable children, and improve health outcomes for millions of Americans. Bring your passion for good work and help us make a difference!

Responsibilities

• Collaborate closely with stakeholders and cross‑functional, internal technical teams to gather requirements, document business rules and develop a thorough understanding of the business context and objectives

• Analyze data, create meaningful insights, and present information clearly to stakeholders.

• Leverage experience with Medicare and Medicaid data to build data access and semantic layers for data products

• Develop and optimize data models, both conceptual and physical, to support analytics, reporting, and operational consumption

• Implement data quality, validation, and monitoring frameworks to ensure accuracy and reliability

• Improve end-to-end performance of data workflows

• Develop and maintain cloud-based data infrastructure using AWS services such as S3, Lambda, Glue, Step Functions, CloudWatch, SQS, DynamoDB, SageMaker and Event Bridge

• Collaborate to design secure, scalable, and cost‑optimized data solutions.

• Contribute to cloud governance, security, and best practices

• Design, build, and maintain scalable, reliable ETL/ELT data pipelines using AWS and Snowflake

• Ensure data workflows are modular, testable, and properly version‑controlled.

• Operationalize pipelines with monitoring, alerting, and automated recovery mechanisms

• Meet schedule deadlines and commitments with a high-level of quality of deliverables.