Senior Data Engineer

Index Analytics, LLC, is a rapidly growing, Baltimore-based small business providing health-related consulting services to the federal government. At the center of our company culture is a commitment to instilling a dynamic and employee-friendly place to work. We place a priority on promoting a supportive and collegial team environment and enhancing staff experience through career development and educational opportunities.

Position Overview

Index Analytics is seeking a Sr. Data Engineer to support Government clients to design, build, and optimize scalable data pipelines and cloud-based solutions. The Sr. Data Engineer plays a key role in modernizing the organization’s data ecosystem by architecting data solutions using a contemporary infrastructure.

As part of a cross-functional team including Data Engineers, Software Engineers, Analysts, the engineer will support efforts to design and implement a robust environment capable of ingesting diverse data sources to support advanced analytics and reporting needs. Core responsibilities include defining structural, interface, and business requirements for data solutions; designing relational and non-relational databases and their associated integration components; and implementing a Snowflake-based system with automated data pipelines.

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.

This position requires an in-person interview at our HQ.

Responsibilities

• Collaborate closely with stakeholders, cross‑functional and internal technical teams to gather requirements, document business rules and develop thorough understanding of the business context and objectives.
• Collaborate to design secure, scalable, and cost‑optimized data solutions.
• Design, build, and maintain scalable, reliable ETL/ELT data pipelines using AWS, Snowflake and Snowflake tools.
• Develop and optimize data models, both conceptual and physical, to support analytics, reporting, dashboards and operational consumption.
• Implement data quality, validation, and monitoring frameworks to ensure accuracy and reliability.
• Ensure data workflows are modular, testable, and properly version‑controlled.
• Operationalize pipelines with monitoring, alerting, and automated recovery mechanisms.
• Conduct advanced data analysis using languages such as Python and SQL.
• Develop documentation to include data models, data dictionaries, and data usage guides.
• Improve end-to-end performance of data workflows.
• Build and maintain CI/CD pipelines using Jenkins to support automated testing, deployments, and continuous integration.
• Meet schedule deadlines and commitments with a high-level of quality of deliverables.
• Collaborate with a team of cross-functional resources in an Agile delivery environment to deliver iterative value.