Data Engineer - Secret Clearance

Zantech•Arlington, VA

1d•Onsite

About The Position

Zantech is seeking a Data Engineer for its Technical Infrastructure and Platform Support project. This is an on-site role based in Arlington, Virginia. The Data Engineer implements the established data architecture by integrating data sources, cleansing and validating data, and resolving pipeline failures in an AWS GovCloud environment. The role supports automated pipelines that feed a Data and Analytics Platform from internal Navy systems and external sources, covering 10 to 20 data sources and 1 to 20+ TB of data, with growth of more than 1 TB per year.

Requirements

Active Secret security clearance; the posting also specifies active DoD Secret or higher clearance per contract requirements.
Demonstrated experience building and maintaining ETL/ELT pipelines in a cloud environment.
Proficiency in Python and SQL.
Experience with data cleansing, data quality validation, and integrating structured and unstructured data from multiple sources.
DoDM 8140.03 qualifying certification, such as CompTIA Security+ CE, before starting.

Nice To Haves

Hands-on experience with AWS Glue, Step Functions, Lake Formation, Athena, and RDS.
Experience with Infrastructure as Code, such as Terraform or CloudFormation, applied to data pipelines.
Experience in AWS GovCloud or DoD IL4/IL5 environments.
Familiarity with Advana/Jupiter, Qlik, or Power BI data sources.
AWS certification, such as AWS Certified Data Engineer - Associate.
Experience supporting federal financial or acquisition data.

Responsibilities

Maintain, monitor, and optimize automated ETL/ELT pipelines.
Build and modify pipelines using AWS Glue, Step Functions, Lake Formation, Athena, and RDS.
Write modular, parameterized pipeline code that allows data structures and refresh frequencies to change without rebuilding the core pipeline architecture.
Support scheduled batch processing, time-based interval micro-batches, and user-triggered on-demand refreshes for time-sensitive financial submissions.
Ingest and export data in open, non-proprietary formats, including Parquet, CSV, and JSON.
Perform data cleansing, validation, and quality assurance as new data sources are integrated.
Resolve Tier 3 tickets involving pipeline failures, refresh errors, and database performance issues.
Implement row-level and column-level security controls at the data layer in coordination with the Data Architect.
Document pipeline configurations, data lineage, and operating procedures.