Data Engineer

AnaVation•Huntsville, AL

13d•Onsite

About The Position

AnaVation is seeking a Senior Data Engineer to join our growing Huntsville, Alabama work program. The selected candidate provides support large scale data engineering and migration activities for a major federal modernization program. This role is responsible for designing, developing, optimizing, and operating data pipelines supporting petabyte scale migration, transformation, and storage of structured and unstructured datasets. The Senior Data Engineer ensures data flows are reliable, repeatable, secure, and aligned to architectural standards required for transferring legacy datasets into modern cloud environments.

Requirements

Bachelor’s degree and 8+ years of experience in data engineering, ETL development, or large scale data operations.
Hands on experience building pipelines for structured/unstructured data across enterprise environments.
Strong proficiency in data modeling, transformation logic, and automation.
Familiarity with cloud environments (AWS preferred), DevSecOps tooling, and scripting languages.
Excellent analytical, documentation, and problem solving skills.
Must be able to work full-time on-site at our customer location in Huntsville, Alabama.
Active Top Secret (TS) clearance with eligibility for Sensitive Compartmented Information (SCI) and the ability to obtain a CI polygraph.

Nice To Haves

Experience with petabyte scale or multi system migration programs.
Background supporting national security customers.
Experience with CI/CD integration, automated testing pipelines, or micro service architectures.
Advanced knowledge of ETL frameworks, distributed compute tools, or cloud native data services.

Responsibilities

Design, build, and optimize scalable ETL/ELT pipelines for ingestion, transformation, and migration of large, multi-source datasets.
Develop data models, schemas, mappings, and integration structures supporting legacy-to-cloud migration.
Improve pipeline automation, performance, throughput, reliability, and fault tolerance.
Lead data cleansing, normalization, enrichment, validation, and root-cause analysis for data quality issues.
Partner with QA, Cloud, DevSecOps, Migration, and development teams to integrate and validate data workflows.
Support AWS-based data engineering and ensure compliance with security, logging, auditing, and data-handling requirements.
Mentor data engineers and participate in technical reviews, sprint activities, architecture discussions, and migration planning.
Maintain pipeline diagrams, mapping specifications, data dictionaries, and other technical documentation.
Track migration progress, pipeline performance, data quality, risks, and blockers, and support timely resolution.