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Manager Data Engineering Jobs in Washington (NOW HIRING)

Data Engineer

Chantilly, VA · On-site

$117.20K - $140.80K/yr

Leverage AWS services such as S3, Glue, Lambda, Redshift, EMR, and Kinesis to support data engineering solutions * Design and manage cloud-based data architectures that are secure, scalable, and cost ...

Data Engineer

Herndon, VA · On-site

$117.70K - $141.40K/yr

Leverage AWS services such as S3, Glue, Lambda, Redshift, EMR, and Kinesis to support data engineering solutions * Design and manage cloud-based data architectures that are secure, scalable, and cost ...

Data Engineer

Mclean, VA · On-site

$115.70K - $139K/yr

Leverage AWS services such as S3, Glue, Lambda, Redshift, EMR, and Kinesis to support data engineering solutions * Design and manage cloud-based data architectures that are secure, scalable, and cost ...

Data Engineer

Chantilly, VA · On-site

$117.20K - $140.80K/yr

Leverage AWS services such as S3, Glue, Lambda, Redshift, EMR, and Kinesis to support data engineering solutions * Design and manage cloud-based data architectures that are secure, scalable, and cost ...

Data Engineer

Arlington, VA · On-site

$131.90K - $158.40K/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 ...

Data Engineer

Arlington, VA · On-site

$131.70K - $158.20K/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 ...

Data Engineer

Arlington, VA

$131.90K - $158.40K/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 ...

AWS Data engineer

Owings, MD · On-site

$110.70K - $133K/yr

Leverage AWS services such as EKS, EMR, Glue, HashiCorp Vault, Docker, and Kubernetes for data engineering solutions. * Apply strong SQL knowledge to design and manage data models and warehouse ...

Power BI Data Engineer

Arlington, VA · On-site

$130.80K - $157.10K/yr

The ideal candidate combines strong data engineering expertise with deep knowledge of Power BI ... Develop and manage data integration workflows using tools such as Azure Data Factory, SSIS, or ...

Create and manage Power BI datasets and semantic models * Partner with upstream data teams when complex data engineering is required Collaboration & Stakeholder Support * Work closely with business ...

Sr. Data Engineer

Washington, DC

$129.70K - $155.70K/yr

This role develops and manages data pipelines, ETL processes, and storage solutions that enable ... Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field.

Data Engineer

Mclean, VA

$115.70K - $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 ...

Sr. Data Engineer

Washington, DC

$129.70K - $155.70K/yr

This role develops and manages data pipelines, ETL processes, and storage solutions that enable ... Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field.

Data Engineer

Falls Church, VA · On-site

$122.20K - $146.70K/yr

Experience leading or mentoring data engineering teams * Familiarity with DoD financial management concepts including obligations, disbursements, unliquidated obligations, and fund balance ...

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Manager Data Engineering information

See Washington salary details

$35.1K

$110K

$194.8K

How much do manager data engineering jobs pay per year?

As of May 30, 2026, the average yearly pay for manager data engineering in Washington 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 are the key skills and qualifications needed to thrive as a Manager Data Engineering, and why are they important?

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.

How does a Manager of 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 Manager Data Engineering roles and responsibilities?

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.

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 most commonly searched types of Data Engineering jobs in Washington? The most popular types of Data Engineering jobs in Washington are:
What job categories do people searching Manager Data Engineering jobs in Washington look for? The top searched job categories for Manager Data Engineering jobs in Washington are:
What cities in Washington are hiring for Manager Data Engineering jobs? Cities in Washington with the most Manager Data Engineering job openings:
Infographic showing various Manager Data Engineering job openings in Washington as of May 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $110,026 per year, or $52.9 per hour.

Data Engineer

KDA Consulting Inc

Chantilly, VA • On-site

$117.20K - $140.80K/yr

Full-time

Posted 24 days ago


Job description

KDA Consulting Inc. is seeking a highly skilled Data Engineer to design, build, and maintain scalable data pipelines and architectures supporting mission-critical programs within the Intelligence Community (IC). This role focuses on enabling efficient data processing, analytics, and decision-making by delivering reliable, high-quality data solutions in cloud environments.

The ideal candidate will have strong experience with AWS cloud services, data engineering best practices, and big data technologies, with the ability to operate in a fast-paced, collaborative environment supporting complex mission systems.

Data Pipeline Development & Engineering

  • Design, develop, and maintain scalable ETL/ELT pipelines to ingest, transform, and load data from multiple sources
  • Build and optimize data workflows supporting both batch and real-time processing
  • Ensure high availability and reliability of data pipelines across enterprise systems

AWS Cloud & Data Services

  • Leverage AWS services such as S3, Glue, Lambda, Redshift, EMR, and Kinesis to support data engineering solutions
  • Design and manage cloud-based data architectures that are secure, scalable, and cost-efficient
  • Implement best practices for data storage, partitioning, and lifecycle management

Data Optimization & Performance

  • Optimize data storage and retrieval for performance, scalability, and cost efficiency
  • Implement indexing, partitioning, and query optimization strategies
  • Monitor and troubleshoot data pipeline performance issues

Data Quality & Governance

  • Ensure data accuracy, consistency, and integrity across all data pipelines and systems
  • Implement validation, monitoring, and error-handling mechanisms
  • Support data governance practices and compliance with security and IC standards

Collaboration & Integration

  • Work closely with data scientists, software engineers, and mission stakeholders to support analytics and operational needs
  • Integrate data solutions with enterprise applications, APIs, and downstream analytics platforms
  • Participate in Agile development processes and contribute to continuous improvement efforts

Requirements

Active TS/ SCI W/ Polygraph Required.

Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent experience)

Demonstrated experience in data engineering and pipeline development

Strong experience with AWS data services (e.g., S3, Glue, Redshift, Lambda, EMR)

Proficiency in SQL and Python for data processing and transformation

Experience working with large-scale data sets and big data technologies

Strong analytical and problem-solving skills