Data Engineer (Senior)

Chantilly, VA, US

Actively hiring, first seen by us 2 days ago

Pay: $140,000–170,000/yearAnnual period assumed — pay source
Job Type: Full-Time Target Salary Range*: $140,000 - $170,000 *This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary
Read the full posting
Work setting: Not stated
Employment: Full-time — employment source
Security Clearance: Active TS or higher [Required] Must be able to obtain CI Polygraph Job Type: Full-Time Target Salary Range*: $140,000 - $170,000
Read the full posting

Before you apply

Work authorization: Citizens onlyMust be able to obtain CI Polygraph

What you’ll work on

Full posting

Build secure data ingestion pipelines using open-source, COTS, and GOTS tools
Design, schedule, and optimize automated ETL pipelines
Design and optimize enterprise relational databases
Implement Attribute-Based Access Control at the data layer
Mentor junior team members and set cross-team data standards

From the employer’s posting

Build secure data ingestion pipelines using open-source, COTS, and GOTS technologies.

Design, create, schedule, and optimize automated ETL pipelines.

Design and optimize enterprise relational databases.

Implement Attribute-Based Access Control at the data layer.

Mentor junior team members.

What you’ll bring

All qualifications

Core experience

Active TS clearance or higher; must be able to obtain CI polygraph
Minimum 8 years in data engineering or database design
Bachelor's degree
Strong SQL, relational database design, and ETL/ELT skills
Experience with structured, semi-structured data and visualization technologies

Preferred experience

Experience supporting federal or secure, multi-enclave environments.
Knowledge of data modeling, warehousing, and performance tuning.

Qualification wording

Active TS or higher [Required] Must be able to obtain CI Polygraph

Minimum 8 years of experience in data engineering, database design, or related fields.

Bachelor’s degree. [Required]

Strong skills in relational database design, SQL, and ETL/ELT processing.

Experience working with structured and semi-structured data and visualization technologies.

Experience supporting federal or secure, multi-enclave environments.

Knowledge of data modeling, warehousing, and performance tuning.

Education & alternatives

Education - Bachelor’s degree. [Required] Experience

Apply at Amatriot Group

Posting record

Report an error

Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records: Live
First seen by us: Nov 1, 20262 days ago
Recorded sightings: 4
Last seen by us: Nov 4, 2026
Employer says posted: Oct 14, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

In line with similar jobs

$140K–$170K against $127K–$190K, the middle half of what similar US postings state.

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 2

Early. Similar jobs usually come down between day 5 and day 54.

From 10,736 similar postings that came down. Coming down is not always a hire.

Amatriot Group is hiring

21 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SQL
TypeScript
Docker
Kubernetes
PostgreSQL
FastAPI
React

Where the posting names them

Application Development and Integration - Support UI, backend, and middleware engineering using TypeScript, React, Python, FastAPI, LanceDB, Lance Graph, PostgreSQL, Temporal.io, Docker, and Kubernetes. - Integrate data services with application, retrieval, and AI/GenAI components.

Skills - Strong skills in relational database design, SQL, and ETL/ELT processing. [Required] - Familiarity with high-performance computing and mixed-technology environments. [Required]

- Support air-gapped, hybrid, and on-premises operational environments. - Support container orchestration and distributed systems management using Kubernetes. - Support locally hosted GPU servers and hyperconverged nodes.

Upload resume Add LinkedIn

Your next step

Complete your application on amatriot.clearcompany.com. The employer’s form will show what is required.

Already applied? Track this application

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Location: Chantilly, VA
Security Clearance: Active TS or higher [Required] Must be able to obtain CI Polygraph
Job Type: Full-Time
Target Salary Range*: $140,000 - $170,000

*This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary

Position Overview

The Data Engineer (Senior) supports advanced visual analytic applications by building secure data pipelines, designing and optimizing large relational databases, and enabling high-performance analysis of structured and semi-structured data.

This role improves data workflows, system performance, and secure data practices while supporting advanced AI/GenAI capabilities, multi-database architectures, cross-domain environments, and application integration. The Data Engineer (Senior) also mentors junior team members and contributes to cross-team engineering standards.

Key Responsibilities

Data Processing and Analytics

Develop data processing workflows and analytics supporting desktop and web-based visual analytic tools.
Support large-scale relational data analysis using visualization technologies and high-performance computing.
Improve data workflows, system performance, and analytical efficiency.
Support processing of structured, semi-structured, and unstructured data.

Data Ingestion and Integration

Build secure data ingestion pipelines using open-source, COTS, and GOTS technologies.
Integrate new data systems with existing data warehouses.
Develop and optimize complex data parsing and streamlined ingestion processes.
Support schema-aligned ingestion and normalization of diverse structured and unstructured data.
Improve system performance and functionality across integrated data environments.

Database Design and Security

Design and optimize enterprise relational databases.
Establish standards for database operations and security.
Support vector, graph, relational, and multi-database architectures.
Implement Attribute-Based Access Control at the data layer.
Support provenance and end-to-end data lineage tracking.
Contribute to system optimization and security posture improvements.

ETL and Data Architecture

Design, create, schedule, and optimize automated ETL pipelines.
Support data architecture involving vector, graph, and multi-database orchestration.
Support data modeling, transformation, integration, and normalization.
Maintain traceability across complex data processing workflows.

AI and GenAI Data Engineering

Support multi-model and multi-modality orchestration involving reasoning, perception, memory, and tool execution.
Support temporal, spatial, geographic, quantitative, and computer vision AI implementations.
Support Named Entity Recognition, contextual entity extraction, and entity resolution.
Support multi-step retrieval and structured output generation.
Enable deep source citation and traceable analytic outputs.
Integrate data platforms with reasoning components, retrieval systems, databases, and AI/GenAI services.

Enterprise Infrastructure and Cross-Domain Support

Support air-gapped, hybrid, and on-premises operational environments.
Support container orchestration and distributed systems management using Kubernetes.
Support locally hosted GPU servers and hyperconverged nodes.
Support multitenant Cross-Domain Solutions.

Application Development and Integration

Support UI, backend, and middleware engineering using TypeScript, React, Python, FastAPI, LanceDB, Lance Graph, PostgreSQL, Temporal.io, Docker, and Kubernetes.
Integrate data services with application, retrieval, and AI/GenAI components.
Support solutions using modern programming languages and frameworks.

Mentorship and Cross-Team Standards

Mentor junior team members.
Contribute to cross-team engineering and data standards.
Promote consistent approaches to data architecture, processing, security, and performance.

Qualifications

Education

Bachelor’s degree. [Required]

Experience

Minimum 8 years of experience in data engineering, database design, or related fields. [Required]
Experience working with structured and semi-structured data and visualization technologies. [Required]
Experience improving data workflows, performance, and security. [Required]

Skills

Strong skills in relational database design, SQL, and ETL/ELT processing. [Required]
Familiarity with high-performance computing and mixed-technology environments. [Required]
Strong analytical, communication, and collaboration skills. [Required]

Preferred Qualifications

Experience supporting federal or secure, multi-enclave environments.
Background with advanced visualization platforms or high-volume data processing.
Knowledge of data modeling, warehousing, and performance tuning.

Source details