Data Engineer (Multiple Openings) - Onsite, Washington, DC

BluePath Labs•Washington, DC

1d•$80,500 - $109,250•Onsite

About The Position

BluePath Labs is seeking candidates for multiple mid-level Data Engineer positions supporting a federal client. The role focuses on building and maintaining pipelines that extract, normalize, validate, and integrate data, and developing reliable datasets, interfaces, data models, lineage, and quality checks for dashboards, financial tools, and historical cost and price information. Successful candidates will independently build, validate, troubleshoot, and document pipelines, integrations, and curated datasets. The position is contingent upon contract award; BluePath Labs is seeking qualified candidates for a proposal for an upcoming government contract, and selected applicants may be contacted for further steps if the contract is awarded. The role is onsite in Washington, DC. No active clearance is required, but TS/SCI is preferred, and candidates must be able to obtain and maintain a U.S. Government security clearance.

Requirements

U.S. citizenship.
Four or more years of relevant data engineering experience.
Experience with SQL, scripting, ETL or ELT, data modeling, pipeline development, reconciliation, lineage, data-quality controls, and documentation.
Ability to independently build, validate, troubleshoot, and document pipelines, integrations, and curated datasets; troubleshoot data flows; and validate analytical inputs.
Must be able to obtain and maintain a U.S. Government security clearance.

Nice To Haves

TS/SCI clearance.
Relevant bachelor's degree or permitted equivalent.

Responsibilities

Build and maintain pipelines that extract, normalize, validate, and integrate data for a federal client.
Develop ETL or ELT processes to support reliable data flows and integrations.
Develop and maintain curated datasets, interfaces, and data models for dashboards, financial tools, and historical cost and price information.
Reconcile data and maintain lineage and data-quality controls.
Independently validate and troubleshoot pipelines, integrations, curated datasets, and data flows.
Resolve data-access and integration needs.
Validate analytical inputs and implement quality checks to support reliable datasets.
Document pipelines, integrations, curated datasets, and data-quality controls.
Convert recurring requirements into reusable components.