1

Manager Data Engineering Jobs in Gaithersburg, MD

Data Engineer

Herndon, VA

$117K - $141K/yr

... management, and delivery of structured, semi-structured, and unstructured data. This position applies data engineering best practices to support enterprise ontologies, knowledge graphs, Semantic Web ...

Data Engineer

Herndon, VA · On-site

$117K - $141K/yr

... management, and delivery of structured, semi-structured, and unstructured data. This position applies data engineering best practices to support enterprise ontologies, knowledge graphs, Semantic Web ...

Data Engineer

Herndon, VA

$117K - $141K/yr

... management, and delivery of structured, semi-structured, and unstructured data. This position applies data engineering best practices to support enterprise ontologies, knowledge graphs, Semantic Web ...

Data Engineering Lead

Arlington, VA · On-site

$106K - $221K/yr

Must have: * 8 years of experience in data engineering, data pipeline design, and management * Must meet DoD 8140 requirements * Bachelor's degree (or 4 years of additional equivalent experience) in ...

Data Engineer

Mclean, VA · On-site

$115K - $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

$117K - $140K/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

$117K - $140K/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

$117K - $141K/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 Journeyman

Fairfax, VA · On-site

$116K - $140K/yr

... management and data lineage tracking using catalog and governance tools to provide transparency, auditability, and regulatory compliance for data assets. * Apply secure data engineering practices ...

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 ...

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 ...

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 ...

Showing results 21-40

Manager Data Engineering information

See Gaithersburg, MD salary details

$33.5K

$105K

$185.8K

How much do manager data engineering jobs pay per year?

As of Aug 18, 2026, the average yearly pay for manager data engineering in Gaithersburg, MD is $104,960.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,300.00 and $135,600.00 per year, depending on experience, location, and employer.

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.

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.

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 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 Gaithersburg, MD?

The most popular types of Data Engineering jobs in Gaithersburg, MD are:

What are popular job titles related to Manager Data Engineering jobs in Gaithersburg, MD?

For Manager Data Engineering jobs in Gaithersburg, MD, the most frequently searched job titles are:

What job categories do people searching Manager Data Engineering jobs in Gaithersburg, MD look for?

The top searched job categories for Manager Data Engineering jobs in Gaithersburg, MD are:

What cities near Gaithersburg, MD are hiring for Manager Data Engineering jobs?

Cities near Gaithersburg, MD with the most Manager Data Engineering job openings:

Infographic showing various Manager Data Engineering job openings in Gaithersburg, MD as of August 2026, with employment types broken down into 82% Full Time, 15% Part Time, and 3% Contract. Highlights an 78% Physical, 4% Hybrid, and 18% Remote job distribution, with an average salary of $104,960 per year, or $50.5 per hour.

$117K - $141K/yr

Full-time

Posted 7 days ago


Job description

Who we are.

Platinum Technologies is a Northern Virginia based integrated solutions firm that specializes in Cybersecurity, Cloud and Digital Services to the Public Sector. Our team solves hard problems and helps our Mission Partners achieve their goals. If you are self-motivated, possess demonstrated learning agility, and are passionate about delivering high-quality work products - we want to hear from you.

We lead with technical expertise, but that is just the tip of the iceberg - the 'Why' matters. At Platinum, we don't hire people to do a job. We provide professional and leadership development to complement our self-motivated domain experts. Our teammates are dot-connecting leaders that operate in a mutually accountable environment to deliver thought leadership, expert technical analysis, and quality execution for our clients. 

 

This position requires an active U.S. Government Security Clearance at the TS/SCI level with CI polygraph.

 

You.

Platinum Technologies is seeking a Data Engineering Subject Matter Expert (SME) to join our team. In this position you will provide technical leadership for the design, implementation, and optimization of enterprise data engineering solutions supporting Object-Based Intelligence (OBI) mission requirements, ontology-driven data integration, and advanced analytics.

The Data Engineering Subject Matter Expert serves as the senior technical authority for developing and implementing scalable data architectures, pipelines, and integration frameworks that enable the ingestion, transformation, management, and delivery of structured, semi-structured, and unstructured data. This position applies data engineering best practices to support enterprise ontologies, knowledge graphs, Semantic Web technologies, and AI/ML applications while ensuring data quality, governance, interoperability, and security across diverse mission systems. Working closely with ontology engineers, software engineers, database engineers, data scientists, and Government stakeholders, the Data Engineering SME develops modern data solutions that support mission analytics, knowledge discovery, and decision advantage.

 

 

 

What you get to do.

  • Lead the design, development, and implementation of enterprise data engineering solutions supporting Object-Based Intelligence mission requirements.
  • Design and optimize scalable data pipelines for ingesting, transforming, validating, and integrating data from multiple internal and external sources.
  • Develop data integration frameworks that support enterprise ontologies, knowledge graphs, and Semantic Web technologies, including RDF, OWL, and SPARQL.
  • Collaborate with ontology engineers, software engineers, database engineers, analysts, and Government stakeholders to translate mission requirements into scalable data engineering solutions.
  • Design and implement data architectures supporting cloud-native, distributed, and hybrid computing environments.
  • Establish data quality, metadata management, lineage, and governance processes to ensure consistency, traceability, and interoperability across enterprise data assets.
  • Optimize data processing performance using modern distributed processing frameworks and scalable storage technologies.
  • Support AI/ML initiatives by developing reliable, high-quality data pipelines that provide curated datasets and semantic context for model training, inference, and decision support.
  • Develop automated monitoring, validation, and testing capabilities to ensure data accuracy, completeness, and operational reliability.
  • Produce and maintain technical documentation, data flow diagrams, interface specifications, data dictionaries, and engineering standards.
  • Provide technical leadership, mentoring, and knowledge transfer activities to Government personnel and project team members regarding data engineering best practices, modern data architectures, and enterprise integration strategies.

Required Skills.

  • Must be a U.S. citizen and have an active TS/SCI with CI polygraph.
  • Minimum twelve (12) years of experience and an advanced degree or 17 years of experience with a bachelor's degree.
  • Demonstrated experience designing and implementing enterprise-scale data engineering solutions and data integration architectures.
  • Experience developing ETL/ELT pipelines using modern data engineering tools and frameworks.
  • Experience integrating structured, semi-structured, and unstructured data from heterogeneous enterprise data sources.
  • Experience with relational databases, NoSQL databases, graph databases, and distributed data processing platforms.
  • Knowledge of data modeling, metadata management, data governance, and enterprise data architecture principles.
  • Familiarity with Semantic Web technologies, knowledge graphs, or ontology-based data integration.
  • Experience supporting cloud-based or containerized data platforms, including Kubernetes and OpenShift.
  • Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders.

 

The Company is an Equal Opportunity/Affirmative Action employer. All qualified candidates will receive consideration for employment without regard to disability, protected veteran status, race, color, religious creed, national origin, citizenship, marital status, sex, sexual orientation/gender identity, age, or genetic information.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
apply for this job