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Manager Data Engineering Jobs in Washington, DC (NOW HIRING)

Elder Research

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

You will work directly with IRS stakeholders, program managers, data scientists, and technical teams to translate complex business and compliance needs into reliable data engineering solutions. Your ...

Elder Research

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

You will work directly with IRS stakeholders, program managers, data scientists, and technical teams to translate complex business and compliance needs into reliable data engineering solutions. Your ...

Pantheon Data

Data Engineer

Washington, DC · On-site

$80K - $120K/yr

Support metadata management and data governance initiatives. * Collaborate with analysts, data scientists, and stakeholders. Required Skills and Experience * Bachelor's degree in Data Engineering ...

Pantheon Data

Data Engineer

Washington, DC · On-site

$80K - $120K/yr

Support metadata management and data governance initiatives.Collaborate with analysts, data scientists, and stakeholders.Required Skills and ExperienceBachelor's degree in Data Engineering, Computer ...

Highspring

Manager, Data & Analytics

Mclean, VA · On-site

Deliver on projects in the areas of data management, data governance, dashboard monitoring, DQ ... Experience programming in Python, SQL, and/or R. * Experience using GitHub (e.g., source code ...

Highspring

Manager, Data & Analytics

Mclean, VA · On-site

Deliver on projects in the areas of data management, data governance, dashboard monitoring, DQ ... Experience programming in Python, SQL, and/or R. * Experience using GitHub (e.g., source code ...

CyberMedia Technologies

Data Engineer

Mclean, VA

$115K - $139K/yr

Familiarity with data governance, metadata management, and data security best practices. * Experience with source control and CI/CD pipelines for data engineering and Databricks workflows. * Working ...

Excella

Lead Consultant Data Engineer (DHS)

Arlington, VA

$131K - $158K/yr

... manage data processes to ensure availability and usability. * Create and automate data pipelines and platforms. * Write clean, efficient, and well-documented code to support data engineering ...

Fantom Corporation

Data Engineer

Mclean, VA · On-site

$115K - $139K/yr

Develop robust Python applications and automation scripts to support data engineering initiatives * Deploy and manage data pipelines using workflow orchestration platforms such as AWS Step Functions ...

The Washington Post

Senior Data Engineer

Washington, DC · On-site

$120K - $163K/yr

... engineering team. * Project Management: Collaborate with Product, Design, Newsroom and business ... Experience with AWS Data Lakehouse technologies including Redshift, Athena, EMR, and Glue catalog.

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Showing results 41-60

All JobsData Engineering JobsManager Data Engineering JobsManager Data Engineering Jobs in Washington, DC

Manager Data Engineering information

See Washington, DC salary details

$35.1K

$110K

$194.8K

How much do manager data engineering jobs pay per year?

As of Aug 12, 2026, the average yearly pay for manager data engineering in Washington, DC is $110,026.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,800.00 and $142,100.00 per year, depending on experience, location, and employer.

What is the difference between Manager Data Engineering vs Data Engineer?

AspectManager Data EngineeringData Engineer
Required CredentialsBachelor's or Master's in CS, Data Science, or related; often leadership experienceBachelor's or higher in CS, IT, or related; technical certifications optional
Work EnvironmentTeam leadership, project management, strategic planningData pipeline development, coding, data modeling
Employer & Industry UsageTech companies, finance, healthcare, where data teams are commonData-focused roles across various industries

The main difference is that Manager Data Engineering oversees data teams and projects, focusing on strategy and leadership, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Managers typically have more experience and leadership skills, whereas Data Engineers are more hands-on with coding and data architecture.

What are the key skills and qualifications needed to thrive as a manager data engineering?

To thrive as a Manager Data Engineering, you need expertise in data architecture, advanced analytics, and leadership, typically supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), data warehousing systems, cloud platforms (AWS, Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong communication, problem-solving, and team management skills help drive project success and foster collaboration. These skills ensure effective data solutions, alignment with business goals, and the ability to lead and grow high-performing engineering teams.

What are the roles and responsibilities of a manager data engineering?

A Manager Data Engineering oversees teams that design, build, and maintain data infrastructure and pipelines for organizations. They are responsible for ensuring the efficient flow and storage of data, implementing best practices in data management, and collaborating with stakeholders to meet business data needs. Additionally, they mentor and guide data engineers, manage project timelines, and ensure data security and quality standards are met. Their role often involves strategic planning to enable data-driven decision making across the company.

How does a manager data engineering typically collaborate with data scientists and business stakeholders?

A Manager of Data Engineering often serves as a bridge between technical teams and business stakeholders. They work closely with data scientists to ensure that data pipelines and infrastructure meet analytical needs, while also translating business requirements into actionable engineering solutions. Regular coordination meetings, clear documentation, and cross-functional projects are common, enabling seamless collaboration and alignment on goals. This role requires strong communication skills and the ability to balance technical priorities with business objectives.
What are the most commonly searched types of Data Engineering jobs in Washington, DC? The most popular types of Data Engineering jobs in Washington, DC are:
What are popular job titles related to Manager Data Engineering jobs in Washington, DC? For Manager Data Engineering jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Manager Data Engineering jobs in Washington, DC look for? The top searched job categories for Manager Data Engineering jobs in Washington, DC are:
Manager Data Engineering jobs near you

Data Engineer

Elder Research

Arlington, VA • On-site

$131K - $158K/yr

Full-time

Re-posted 29 days ago

Job description

Data Engineer
General Information
Requisition # 675
Locations USA-VA-Arlington
Posting Date 03/04/2026
Security Clearance Required - IRS MBI
Remote Type Hybrid
Time Type Full time
Description & Requirements
Elder Research Inc., a wholly owned subsidiary of MANTECH international Corporation seeks a motivated, career and customer-oriented Data Engineer to join our team in Arlington, VA. This is a hybrid position Preferably located in the Washington DC area.
As a Data Engineer, you will support the Internal Revenue Service's mission to combat tax fraud, identity theft, and non-compliance by designing and delivering secure, scalable, and automated data pipelines that power advanced analytics, machine learning models, and decision-support tools. You will work directly with IRS stakeholders, program managers, data scientists, and technical teams to translate complex business and compliance needs into reliable data engineering solutions.
Your work will enable fraud detection, audit prioritization, refund review, and compliance risk analysis across large, sensitive tax and financial datasets. This role sits within an analytics-focused business unit supporting IRS enforcement, compliance, and research initiatives, partnering closely with data science and analytics teams to ensure data products are production-ready, trustworthy, and mission-aligned.
Responsibilities include but are not limited to:
  • Troubleshoot and resolve complex data and system issues across cross-functional and mission-critical environments with minimal supervision
  • Engineer solutions that integrate diverse data types, including transactional, financial, and textual data, to support compliance and fraud analytics
  • Collaborate with data scientists and stakeholders to deploy analytics applications, dashboards, and decision-support tools
  • Write, test, and refine reusable, well-documented code in Python, SQL, Java, and other languages using collaborative development practices
  • Build and maintain secure, scalable data pipelines and end-to-end systems, including operation within air-gapped or restricted government environments
  • Support the full engineering lifecycle, from concept and design through deployment, monitoring, and ongoing support
  • Produce technical documentation and deliver briefings or presentations to technical and non-technical audiences
  • Act as a technical consultant, translating business, compliance, and enforcement needs into effective data solutions

Minimum Qualifications:
  • 2-7+ years of experience in data science, analytics, or a related technical field, with prior programming experience, preferably in Python
  • Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, data engineering, business, or social sciences
  • Design, build, and deploy robust, repeatable, and automated data pipelines using Python and SQL to transform raw data into analytics and ML-ready datasets
  • Engineer data pipelines that support fraud detection, compliance analytics, and predictive risk modeling across structured and unstructured data sources in Databricks
  • Develop and maintain end-to-end machine learning data workflows across on-premises and cloud environments, integrating backend systems with analytics platforms and user-facing applications
  • Partner closely with data scientists, analysts, product managers, and government stakeholders to align data engineering solutions with IRS mission objectives, and translate client and stakeholder requirements into clear, actionable technical designs and implementation plans
  • Modernize and optimize data and ML workflows by implementing best practices for scalability, reliability, maintainability, and security, while contributing effectively within agile, fast-paced development environments supporting iterative delivery and continuous improvement
  • Demonstrate a strong willingness to learn new technologies, adapt to evolving requirements, share knowledge across teams, and travel and work on-site with clients as project needs require

Preferred Qualifications:
  • Advanced degree (MS) in analytics, computer science, data science, mathematics, statistics, engineering, management information systems, decision science, or related fields
  • Experience with version control systems (Git, SVN, Mercurial) and collaborative programming practices (pair programming, code reviews), as well as containerization and environment management (venv, conda)
  • Experience with platforms and technologies such as Databricks and AWS, including prior Databricks experience in Unity Catalog, PySpark, Spark SQL, and Jobs
  • Familiarity with vector, object, and document-based data storage systems, and experience implementing data engineering solutions in remote or austere environments, including use of bash and command-line tools
  • Experience with business intelligence and data visualization tools (Power BI, Tableau), and understanding of the data analytics lifecycle (e.g., CRISP-DM) and how engineering supports downstream analytics and ML use case

Clearance Requirements:
  • Must currently possess an IRS Public Trust clearance with Full Background Investigation

Physical Requirements:
  • Must be able to remain in a stationary position 50%
  • Needs to occasionally move about inside the office to access file cabinets, office machinery, etc.
  • Frequently communicates with co-workers, management, and customers, which may involve delivering presentations. Must be able to exchange accurate information in these situations

About Elder Research, Inc - People Centered. Data Driven
Elder Research considers all qualified applicants for employment without regard to disability or veteran status or any other status protected under any federal, state, or local law or regulation.
If you need a reasonable accommodation to apply for a position with Elder Research, please email us at careers@elderresearch.com and provide your name and contact information.

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