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Data Engineering Jobs in Silver Spring, MD (NOW HIRING)

Databricks Data Engineering Manager

Rosslyn, VA · On-site

$130K - $156K/yr

Work you'll do As a Lead Data Engineer II in our AI & Data practice, you will leverage your extensive real-world experience to lead the delivery of transformative data and AI programs for our clients ...

Data Engineer

Washington, DC · On-site

$80K - $120K/yr

Required Skills and ExperienceBachelor's degree in Data Engineering, Computer Science, Software Engineering, or related field.AWS Data Engineer Associate, AWS Certified Data Analytics, Azure Data ...

Data Engineer

Washington, DC · On-site

$80K - $120K/yr

Bachelor's degree in Data Engineering, Computer Science, Software Engineering, or related field. * AWS Data Engineer Associate, AWS Certified Data Analytics, Azure Data Engineer Associate, or ...

Showing results 21-40

Data Engineering information

See Silver Spring, MD salary details

$47.6K

$170.6K

$251.7K

How much do data engineering jobs pay per year?

As of Sep 15, 2026, the average yearly pay for data engineering in Silver Spring, MD is $170,592.00, according to ZipRecruiter salary data. Most workers in this role earn between $138,000.00 and $175,700.00 per year, depending on experience, location, and employer.

What is data engineering?

A Data Engineering job involves designing, building, and maintaining the infrastructure that enables efficient data collection, storage, and processing. Data Engineers develop pipelines to transform raw data into usable formats for analytics and machine learning. They work with databases, big data technologies, and cloud platforms to ensure data is accessible and reliable. Their role is crucial for organizations to make data-driven decisions and optimize business processes.

What does a data engineer do?

Data Engineers regularly design, build, and maintain scalable data pipelines to support analytics and business intelligence teams. Their daily tasks often involve working with large datasets, optimizing data storage, ensuring data integrity, and troubleshooting data-related issues. Collaboration with data scientists, analysts, and software engineers is common to align on data requirements and improve workflows. You may also participate in regular code reviews and contribute to the ongoing improvement of data infrastructure. This role is ideal for problem-solvers who enjoy working with both code and complex systems in a collaborative, fast-paced environment.

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

To thrive in Data Engineering, you need a solid background in programming (such as Python, Java, or Scala), data modeling, and database management, typically supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms like AWS or Azure, big data frameworks (e.g., Hadoop, Spark), and relevant certifications is highly valued. Strong problem-solving abilities, effective communication, and the ability to work collaboratively across teams are key soft skills for this role. These attributes are crucial for designing robust data pipelines, ensuring data quality, and enabling organizations to make data-driven decisions efficiently.

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. They typically need skills in SQL, cloud platforms, and tools like Apache Spark or Hadoop, and job opportunities are expected to remain strong as organizations continue to prioritize data infrastructure.

What are the most commonly searched types of Data Engineering jobs in Silver Spring, MD?

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

What are popular job titles related to Data Engineering jobs in Silver Spring, MD?

For Data Engineering jobs in Silver Spring, MD, the most frequently searched job titles are:

What job categories do people searching Data Engineering jobs in Silver Spring, MD look for?

The top searched job categories for Data Engineering jobs in Silver Spring, MD are:

What cities near Silver Spring, MD are hiring for Data Engineering jobs?

Cities near Silver Spring, MD with the most Data Engineering job openings:

Infographic showing various Data Engineering job openings in Silver Spring, MD as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 81% Full Time, 14% Part Time, 1% Temporary, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $170,592 per year, or $82 per hour.

Fellow, Data Engineering

Alexandria, VA • On-site

Other

Medical, Life, Retirement

Posted 13 days ago


Job description

Overview

Systems Planning and Analysis, Inc. (SPA) delivers high-impact technical solutions to complex national security issues. With over 50 years of business expertise and consistent growth, SPA is known for continuous innovation for its government customers, both in the U.S. and abroad. The company’s Fellows program aligns positions with capabilities and domains across all divisions. The Data Engineering Fellow serves as the corporate lead responsible for strategic leadership, guidance, and mentoring in data‑driven engineering, analytics, and architectures.

The Data Engineering Fellow reports to the Chief Capabilities Office (CCO) and will design and mature robust data architectures and analytic approaches that leverage structured, semi‑structured, and unstructured data to deliver actionable insights. This is a fractional, part‑time role expected to average approximately 40 hours per quarter (roughly one week of full‑time effort every three months), focused on high‑impact strategic contributions rather than day‑to‑day operations.

Responsibilities
  • Cultivation of market‑relevant SPA expertise in data engineering and analytics
    • Define expert knowledge and skills across Beginner, Intermediate, and Advanced levels, sustaining structured repositories including white papers, case studies, and pedigreed data sets. Implement quality assurance within training, products, and development processes related to data engineering. Define an expertise assessment process leading to tiered certifications for the Capability.
    • Ensure high‑quality training at all expert levels by promoting best practices, emerging techniques, and professional development across SPA. Provide training through a community of practice and encourage personal expertise growth.
  • Market & Client Visibility
    • Represent SPA expertise across market/client platforms, conferences, and social media.
    • Participate in strategy sessions for data‑driven solutions on high‑priority opportunities and support proposal development by contributing insights or identifying expertise partners.
    • Train the team in client engagement, professional presentations, and writing, supporting customer meetings and engagements as appropriate to the capture and business development process.
  • Be at the cutting edge
    • Lead forward‑looking initiatives that support innovation, stay ahead of market trends, and position SPA as an industry thought leader. Focus areas include:
    • Strategic data and analytics guidance: Provide periodic strategic guidance on SPA’s enterprise data engineering and analytics strategy, ensuring alignment with government customer mission requirements and federal priorities.
    • Architecture and technical review: Review and advise on the design of data platforms and pipelines, including data lakes, warehouses, and streaming architecture.
    • Data governance and best practices: Advise on data modeling, quality, storage, and governance frameworks in alignment with federal data policies.
    • Advanced data engineering, analytics, and predictive modeling: Provide expert input on data curation, ingestion, normalization, and labeling for statistical models and machine learning solutions.
    • Visualization and decision support: Advise on the design of dashboards, geospatial products, and interactive visualizations that support senior decision‑makers.
  • Data Engineering Support for Artificial Intelligence
    • Assist the Applied AI Fellow in incorporating data engineering best practices into emerging AI methods and architectures, guiding the curation and labeling of data to support AI enablement.
Qualifications Required Qualifications
  • Active DoD Secret clearance with the ability to obtain and maintain a Top Secret clearance.
  • Bachelor’s degree in Computer Science, Data Engineering, Software Engineering, Information Systems, Engineering, Mathematics, or a related technical discipline.
  • 15+ years of progressively responsible experience in data engineering, enterprise data architecture, analytics, or related technical leadership roles.
  • Demonstrated national‑level technical leadership and recognition as a subject matter expert in data engineering, enterprise data architecture, or advanced analytics.
  • Extensive experience designing, evaluating, and advising on enterprise‑scale data architectures supporting structured, semi‑structured, and unstructured data.
  • Deep experience with data platforms, data lakes, data warehouses, ETL/ELT pipelines, streaming architectures, cloud‑native data ecosystems, and modern data integration practices.
  • Experience supporting U.S. Government, DoD, Intelligence Community, or other federal customers.
  • Deep understanding of data governance, metadata management, data quality, master data management, data security, and federal data standards and policies.
  • Demonstrated experience enabling advanced analytics, AI, machine learning, and predictive analytics through scalable data engineering practices.
  • Proven ability to provide strategic technical guidance to executive leadership, chief engineers, program managers, and multidisciplinary engineering teams.
  • Demonstrated experience mentoring technical professionals, developing communities of practice, and building organizational capability through training and knowledge sharing.
  • Excellent written and verbal communication skills, including experience authoring technical white papers, strategy documents, executive briefings, and proposal content.
Desired Qualifications
  • Master’s or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Engineering, Applied Mathematics, or a related technical discipline.
  • Active Top Secret/SCI security clearance.
  • Experience architecting secure cloud‑based data solutions within AWS, Microsoft Azure, Google Cloud, GovCloud, or classified cloud environments.
  • Expertise with modern data engineering platforms and technologies such as Databricks, Snowflake, Apache Spark, Kafka, Airflow, dbt, Delta Lake, or comparable technologies.
  • Experience supporting national security missions involving defense, intelligence, cyber, space, or homeland security.
  • Familiarity with the DoD Digital Engineering Strategy, DoD Data Strategy, CJADC2, Digital Twins, MBSE, or related digital transformation initiatives.
  • Experience establishing enterprise data governance frameworks, reference architectures, technical standards, and best practices.
  • Relevant professional certifications (e.g., AWS Certified Data Engineer, Microsoft Azure Data Engineer Associate, Google Professional Data Engineer, Databricks Certified Data Engineer, Snowflake SnowPro, DAMA CDMP, TOGAF).
  • Established professional relationships across government, industry, academia, and professional organizations that enhance SPA’s visibility and technical leadership.
Benefits and Pay Range

SPA offers a competitive base pay and variable compensation opportunities. Eligible employees may enroll in health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance, and paid and unpaid time‑away programs. Compensation is commensurate with experience and qualifications. Pay Transparency Range: USD $175,000 – $265,000 per year.

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