Senior Data Engineer

INDEX ANALYTICS LLC•Milford Mill, MD

13d•$131,100 - $173,250•Onsite

About The Position

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.

Requirements

US citizen or lived in the US for 3 of the last 5 years.
Must be able to obtain a U.S. Federal government client badge and pass a government background investigation.
Bachelor’s degree or equivalent with ten (10) or more years of experience as Data System Architect, Engineer or similar role.
Hands-on experience using Snowflake tools, SQL and Python is required.
Strong proficiency in Snowflake, AWS services as well as with GitHub for source control, branching strategy and reviews.
Knowledge of data integration patterns, data warehousing, and modern data architecture.
Strong analytical and communication skills, including the ability to analyze data, create meaningful insights, and present information clearly to stakeholders.
Experience with object‑oriented programming and building with software engineering principles.
DevOps exposure, including CI/CD tools like Jenkins.
Understanding of Data Lake concepts.
Knowledge of Agile framework, Scrum methodologies and tools used to support them.
Strong written and verbal communication skills are required, ability to collaborate, present, and report to stakeholders on findings.

Nice To Haves

Prior experience with government agencies and fraud detection systems is a plus.

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.