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Data Engineer Ml Jobs in Washington (NOW HIRING)

Senior Data Engineer

Reston, VA · On-site

$140K - $160K/yr

Experience with AWS, vector search, document data, or AI/ML data pipelines is valuable, but the core requirement is strong data engineering judgment: knowing how to move, structure, validate, and ...

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

Working with software engineers, AI/ML engineers, cybersecurity teams, and mission stakeholders ... Data Engineer II or III WHY 540? 540 is a forward-thinking company that the government turns to in ...

Senior Data Engineer

Reston, VA

$110K - $149K/yr

Experience with AWS, vector search, document data, or AI/ML data pipelines is valuable, but the core requirement is strong data engineering judgment: knowing how to move, structure, validate, and ...

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

Working with software engineers, AI/ML engineers, cybersecurity teams, and mission stakeholders ... Data Engineer II or III WHY 540? 540 is a forward-thinking company that the government turns to in ...

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

Data Engineer General Information Requisition # 675 Locations USA-VA-Arlington Posting Date 03/04 ... Modernize and optimize data and ML workflows by implementing best practices for scalability ...

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

Data Engineer General Information Requisition # 675 Locations USA-VA-Arlington Posting Date 03/04 ... Modernize and optimize data and ML workflows by implementing best practices for scalability ...

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

Data Engineer General Information Requisition #710 Locations USA-VA-Arlington Posting Date 06/12 ... Modernize and optimize data and ML workflows by implementing best practices for scalability ...

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

Working with software engineers, AI/ML engineers, cybersecurity teams, and mission stakeholders ... Data Engineer II or III WHY 540? 540 is a forward-thinking company that the government turns to in ...

Data Engineer

Washington, DC · On-site

$125 - $150/hr

As a data engineer, you know that organizing data can yield pivotal insights when it's gathered ... ML TS/SCI clearance with a polygraph Bachelor's degree and 8+ years of experience in data ...

AI Data Engineer

Fort Belvoir, VA · On-site +1

$160K - $200K/yr

The AI Data Engineer will design, develop, and maintain data pipelines and architectures to support AI/ML workloads for the Army Intelligence & Security Enterprise (AISE). This role ensures data ...

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

As a Data Engineer, you will support the Internal Revenue Service's mission to combat tax fraud ... Modernize and optimize data and ML workflows by implementing best practices for scalability ...

Data Engineer

Arlington, VA

$131K - $158K/yr

As a Data Engineer, you will support the Internal Revenue Service's mission to combat tax fraud ... Modernize and optimize data and ML workflows by implementing best practices for scalability ...

Data Engineer

Chantilly, VA · On-site

$117K - $140K/yr

Closure Technologies is seeking a Data Engineer that will leverage their development skills and ... Preferred Qualifications: * Experience deploying systems that leverage AI/ML technology

AI Data Engineer

Fort Belvoir, VA · On-site

$160K - $200K/yr

The AI Data Engineer will design, develop, and maintain data pipelines and architectures to support AI/ML workloads for the Army Intelligence & Security Enterprise (AISE). This role ensures data ...

Showing results 41-60

Data Engineer Ml information

What does a data engineer ML do?

A Data Engineer ML (Machine Learning) is responsible for designing, building, and maintaining the data pipelines and infrastructure necessary for machine learning applications. They clean, process, and organize large datasets to ensure data quality and accessibility for data scientists and ML engineers. In addition, they may work on deploying machine learning models to production environments and optimizing data workflows for efficiency and scalability.

What are the key skills and qualifications needed to thrive as a data engineer ML?

To thrive as a Data Engineer ML, you need strong programming skills (especially in Python or Scala), knowledge of data modeling, and a solid foundation in database technologies, typically supported by a degree in computer science or a related field. Familiarity with big data frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and ETL tools, as well as relevant certifications, is highly beneficial. Excellent problem-solving abilities, teamwork, and clear communication help you collaborate with data scientists and stakeholders effectively. These skills are essential for building robust data pipelines and infrastructure that enable scalable, high-quality machine learning solutions.

How do data engineer ML roles typically collaborate with data scientists and machine learning engineers on projects?

Data Engineer ML professionals work closely with data scientists and machine learning engineers by building and maintaining robust data pipelines, ensuring clean and reliable datasets are readily available for modeling and analysis. They often participate in meetings to understand model requirements, help optimize data storage for performance, and support the deployment of machine learning models into production environments. Effective collaboration involves continuous communication to troubleshoot data issues, implement data validation, and scale solutions as project needs evolve. This teamwork ensures that data-driven projects move efficiently from experimentation to deployment.

What is the difference between Data Engineer Ml vs Data Scientist?

AspectData Engineer MlData Scientist
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science certifications
Work EnvironmentBuilding data pipelines, managing databasesAnalyzing data, creating models
Employer & Industry UsageTech companies, finance, healthcareResearch institutions, tech firms, finance

Data Engineer Ml focuses on developing and maintaining data infrastructure and pipelines, while Data Scientists analyze data and build predictive models. Both roles often collaborate but serve different functions within data teams.

What cities in Washington are hiring for Data Engineer Ml jobs?

Cities in Washington with the most Data Engineer Ml job openings:

Infographic showing various Data Engineer Ml job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Senior Data Engineer

Pantheon Data

Reston, VA • On-site

$140K - $160K/yr

Full-time

Posted 12 days ago


Job description

Company Overview
Pantheon Data (a Kenific Holding company) is a private, small business based in the Washington, DC, area. Pantheon Data was founded in 2011, initially providing acquisition and supply chain management services to the US Coast Guard. Our service offerings have grown in the past ten years, including infrastructure resiliency, contact center operations, information technology, software engineering, program management, strategic communications, engineering, and cybersecurity. We have also grown our customer base to include commercial clients. The company has used this experience to expand our service offerings to other agencies within the Department of Homeland Security (DHS), the Department of Defense (DoD), and other Federal Civilian Agencies.
Position Overview
We are seeking a hands-on Data Engineer to help design, build, and operate the data foundations that support advanced analytics, AI/ML, and intelligent document processing solutions. The right candidate is a strong engineer who understands how data moves through real systems: ingestion, orchestration, transformation, quality checks, storage, query patterns, operational monitoring, and delivery to downstream applications. This person should be comfortable working across structured, semi-structured, and unstructured data, and should bring the judgment to build pipelines that are reliable, explainable, maintainable, and useful to the engineering teams and products that depend on them.
The ideal candidate has strong Python and SQL skills, understands when data should be modeled for operational use versus analytical use, and can reason clearly about batch processing, event-driven pipelines, data quality, lineage, and downstream consumption. They should be able to become productive quickly in a complex engineering environment, ask good questions, and build systems that other engineers can trust and extend. Experience with AWS, vector search, document data, or AI/ML data pipelines is valuable, but the core requirement is strong data engineering judgment: knowing how to move, structure, validate, and serve data reliably in support of real products and mission needs.
Responsibilities
  • Design, build, and maintain reliable data pipelines for structured, semi-structured, and unstructured data sources.
  • Develop Python-based processing workflows for data ingestion, normalization, validation, enrichment, and transformation.
  • Work with SQL and relational data stores to support transactional, analytical, and application-facing use cases.
  • Help design data models and storage patterns appropriate to the workload, including OLTP, OLAP, object storage, document-oriented, search, vector, or graph-oriented patterns when applicable.
  • Implement orchestration and scheduling for repeatable data workflows using tools such as Airflow, AWS Step Functions, Dagster, Prefect, Glue workflows, or similar technologies.
  • Build automated quality checks, reconciliation logic, validation reports, and operational alerts so data issues are detected early and can be diagnosed quickly.
  • Support data pipelines that feed AI/ML, retrieval, document intelligence, analytics, and application workflows.
  • Collaborate with machine learning engineers, software engineers, cloud engineers, and product stakeholders to turn ambiguous data problems into working software.
  • Write maintainable code, participate in code reviews, document data flows, and contribute to engineering standards for testing, deployment, observability, and version control.
  • Help improve the velocity of a growing engineering team by taking ownership of well-scoped data engineering work while continuing to grow into broader system ownership.

Required Skills and Experience
  • Bachelor's degree in Computer Science, Engineering, or a related technical field from an ABET accredited university.
  • 5+ years of professional hands-on data engineering, software engineering, analytics engineering, or closely related experience.
  • Strong Python programming skills, including experience writing maintainable production-oriented code rather than only notebooks or one-off scripts.
  • Strong SQL skills and practical understanding of data modeling, query performance, joins, indexing, schemas, normalization/denormalization, and data quality.
  • Understanding of core data engineering concepts, including batch processing, event-driven workflows, ETL/ELT, orchestration, idempotency, retries, backfills, lineage, and failure handling.
  • Working knowledge of OLTP versus OLAP systems and the tradeoffs between transactional databases, analytical stores, object storage, and search-oriented systems.
  • Experience building or supporting data pipelines that move data between systems, such as APIs, databases, files, object storage, queues, warehouses, or downstream applications.
  • Ability to reason about data correctness, schema changes, validation, reconciliation, duplicate handling, missing data, and operational recovery.
  • Comfortable working with Git, pull requests, code review, issue tracking, documentation, and collaborative software development practices.
  • Strong communication skills and the ability to explain data flow, design choices, limitations, and tradeoffs to both technical and non-technical stakeholders.
  • Ability to work effectively in a distributed, cross-functional engineering environment and produce high-quality work with limited hand-holding.
  • Ability to meet deadlines.
  • Proficient in Microsoft Suite software including Outlook, Word, Excel, SharePoint, and PowerPoint.

Preferred Skills and Experience
  • AWS data services such as S3, Lambda, Glue, Athena, Step Functions, SQS/SNS, Kinesis, EMR, RDS, DynamoDB, Redshift, OpenSearch, or CloudWatch.
  • Experience with workflow orchestration tools such as Airflow, Dagster, Prefect, AWS Step Functions, Glue, or similar.
  • Experience with PySpark, Spark, Databricks, EMR, Snowflake, Redshift, or other distributed/analytical data platforms.
  • Experience supporting AI/ML or RAG-style data workflows, including metadata enrichment, retrieval datasets, vector search, embeddings, evaluation datasets, or human validation workflows.
  • Experience with document-oriented or unstructured data pipelines, including PDFs, OCR output, tables, forms, images, extracted text, metadata, or search indexes.
  • Experience with graph databases or graph-shaped data models is a plus.
  • Experience with Docker, CI/CD, infrastructure as code, automated testing, logging, monitoring, and production support is a plus.
  • Familiarity with data governance, access control, PII handling, auditability, lineage, and compliance-sensitive environments.

Clearance Requirements
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements. Secret Clearance is required for continued employment.
Work Location: Reston, VA - Remote
  • Our company prioritizes the benefits of flexibility and collaboration, whether that happens in person or remotely.
  • If the position is remote or hybrid, you may periodically work from a Pantheon Data office location or client site.
  • If this position is assigned to a Pantheon Data office location or client site, you'll work with colleagues and clients in person, as needed for specific client requirements.

Interview Requirement: Candidates who are local to the area should be prepared to participate in an in-person interview as part of the selection process. Candidates outside the local area may be considered for a virtual interview.
Compensation
The salary range for this position is $140,000 - $160,000. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.
Benefits Overview
We are always looking for good people! Pantheon Data is committed to providing its employees with competitive salaries and benefits in order to increase employee satisfaction and productivity. In addition to our benefits, we also offer SmartBenefits through the Washington Metro Area Transportation Authority, where you specify an amount of your pre-tax wages be paid directly to your SmarTrip account. In some cases, tuition assistance may be available for continuing education expenses and certifications related to their position. Additional details may be found at
Pantheon Data Important Information
All qualified applicants will be considered for employment without regard to disability, status as a protected veteran, or any other status protected by applicable federal, state, local, or international law.
As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to our Talent Team at or by phone (571) 363-4020.
This company uses E-Verify to confirm each employee's work authorization. For more information, click here