Data Center Operations Jobs in District of Columbia
Data Center Operations jobs in District of Columbia concentrate heavily in the federal government contracting, defense IT, and telecommunications sectors, with demand running from entry-level technicians to senior infrastructure engineers. Washington D.C. is the dominant hiring metro, anchored by major contractors and agencies, with notable activity in Northern Virginia adjacent markets that cross into D.C.-based operations. Employers with a lasting presence hiring in this space include Leidos, SAIC, and General Dynamics IT, with the most in-demand specialties being network infrastructure management, systems monitoring, and physical security compliance. Find a role that fits below and apply directly.
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Showing 5 of 342+ Data Center Operations jobs
About the Role
As an Associate Client Data Engineer at CredLens, you will focus on the client-onboarding workflow that brings new credential-issuer data into our platform. You will learn the platform and the fundamentals of production data engineering with direct support from more senior engineers, and gain hands-on experience across the full onboarding workflow, with a clear path to grow into a broader data-engineering role over time. Because so much of the work involves direct client interaction, excellent customer-service skills and clear communication are essential.
This is an early-career, hands-on role focused exclusively on onboarding: partnering directly with clients to receive their data, understanding and documenting the data structure, and cleaning, transforming, and validating the data so it is ready for CredLens' data pipeline. This is an excellent opportunity to start a data career from the ground level by continuing to build a data engineering skillset while working in a role that directly impacts end users. You will work within a small, cohesive Data Engineering team, reporting to the Data Engineering Team Lead. The team is based in Washington, DC. This is a hybrid role requiring in-person attendance at the office at least two days a week, likely Tuesdays and Thursdays.
Note: this is not a "big data" or "real-time" analytics role. It best suits a mission-aligned individual who cares about using data to create more equitable outcomes and who focuses on quality, reliability, and a smooth client experience.
Context
CredLens is building a nonprofit national data trust focused on verified outcomes for non-degree credentials. The effort is an initiative launched by the Strada Education Foundation in 2024. CredLens will deliver actionable insights and power ongoing research for industry-based, professional, and workforce credentials.
CredLens is designed to fill the data gap for non-degree credentials. The attainment of these credentials is growing, but there is little to no data tracking their outcomes. CredLens will offer tailored data analytics and visualizations to credential issuers, workforce training providers, philanthropic funding partnerships, and state system partnerships to support the continuous improvement of credential quality and to support informed funding and scaling decisions.
Key Responsibilities
Core responsibility areas, listed below with the approximate time required for execution in the first 12 - 18 months of work if the incumbent is new to the role:
Serve as the data engineering point of contact for new clients during onboarding, guiding them through what data to provide and in what format.
Receive incoming client data and perform exploratory data analysis to understand its structure, quality, and completeness.
Identify and flag missing, malformed, or inconsistent fields early, and coordinate with the client to resolve them.
Clean, transform, and validate client data so it conforms to CredLens' standards and is ready for downstream ingestion.
Build and run the models and transformations that move a client's data through the onboarding stages of the pipeline, using SQL, Python, DBT, and Airflow.
Document each client's onboarding: data sources, decisions made, and any exceptions, contributing to shared onboarding procedures and templates.
Track onboarding progress and time, and surface areas of friction to improve the process so that it becomes faster and more repeatable over time.
Work with the broader Data Engineering team to research, learn, and implement new improvements to the onboarding pipeline’s efficiency & scalability so it can grow with us.
Qualifications and Experience
Education
Bachelor's degree in computer science, information systems, data science, or a related field is required. OR, equivalent practical experience is required, at least two years.
Experience Required
Suitable for a new or recent graduate; no prior professional experience required. Internships, academic projects, or other hands-on data work are a plus, as is a demonstrated ability to learn quickly.
Working proficiency in SQL and Python for data manipulation and analysis.
Some past experience working with and cleaning raw datasets.
Strong customer-service orientation and the ability to communicate clearly with non-technical clients.
Attention to detail, particularly around data quality, validation, and documentation.
Consistently takes initiative to learn and try new things, and keeps a mindset of constant improvement.
Experience Preferred
Exposure to Redshift, Snowflake, PostgreSQL, or similar databases.
Experience with Pandas DataFrames, Jupyter notebooks, and other quick data processing tools.
Familiarity with DBT, Airflow, or other data pipeline and orchestration tooling.
Familiarity with AWS S3 and Lambda functions, or other AWS services.
Experience working with Github, or another code version control platform.
Experience handling sensitive or confidential data and following security best practices.
Experience working in a startup, nonprofit, or mission-driven environment.
Skills Required
SQL
Python
Data cleaning & manipulation
Interpersonal skills
About CredLens
Non-degree credentials are reshaping how people move from learning to earning. Millions of learners are pursuing certificates, bootcamps, and workforce programs as pathways to better jobs and higher wages. But growth has outpaced clarity.
Thousands of offerings, uneven definitions, and fragmented outcomes data make it nearly impossible to distinguish impact from activity. When results are unclear, learners carry the risk, strong programs can't stand out, and investment can't reliably flow to what works.
CredLens exists to fix that.
We are a neutral, trusted source of high-quality outcomes data for non-degree credentials — connecting issuer-verified credential records to real-world employment, earnings, and education outcomes. Our partners use that data to improve programs, guide investment, and strengthen career pathways for learners.
Two years in, we have a firmly established platform, a growing client base, and the backing of Strada Education Foundation. We are not a startup finding its footing. We are a company beginning to scale — and we are building the team that will take us there.
Mission and Value Alignment
Travel Requirements
Approximately 5% domestic travel anticipated.
plus annual bonus
About the Role
As an Associate Client Data Engineer at CredLens, you will focus on the client-onboarding workflow that brings new credential-issuer data into our platform. You will learn the platform and the fundamentals of production data engineering with direct support from more senior engineers, and gain hands-on experience across the full onboarding workflow, with a clear path to grow into a broader data-engineering role over time. Because so much of the work involves direct client interaction, excellent customer-service skills and clear communication are essential.
This is an early-career, hands-on role focused exclusively on onboarding: partnering directly with clients to receive their data, understanding and documenting the data structure, and cleaning, transforming, and validating the data so it is ready for CredLens' data pipeline. This is an excellent opportunity to start a data career from the ground level by continuing to build a data engineering skillset while working in a role that directly impacts end users. You will work within a small, cohesive Data Engineering team, reporting to the Data Engineering Team Lead. The team is based in Washington, DC. This is a hybrid role requiring in-person attendance at the office at least two days a week, likely Tuesdays and Thursdays.
Note: this is not a "big data" or "real-time" analytics role. It best suits a mission-aligned individual who cares about using data to create more equitable outcomes and who focuses on quality, reliability, and a smooth client experience.
Context
CredLens is building a nonprofit national data trust focused on verified outcomes for non-degree credentials. The effort is an initiative launched by the Strada Education Foundation in 2024. CredLens will deliver actionable insights and power ongoing research for industry-based, professional, and workforce credentials.
CredLens is designed to fill the data gap for non-degree credentials. The attainment of these credentials is growing, but there is little to no data tracking their outcomes. CredLens will offer tailored data analytics and visualizations to credential issuers, workforce training providers, philanthropic funding partnerships, and state system partnerships to support the continuous improvement of credential quality and to support informed funding and scaling decisions.
Key Responsibilities
Core responsibility areas, listed below with the approximate time required for execution in the first 12 - 18 months of work if the incumbent is new to the role:
Serve as the data engineering point of contact for new clients during onboarding, guiding them through what data to provide and in what format.
Receive incoming client data and perform exploratory data analysis to understand its structure, quality, and completeness.
Identify and flag missing, malformed, or inconsistent fields early, and coordinate with the client to resolve them.
Clean, transform, and validate client data so it conforms to CredLens' standards and is ready for downstream ingestion.
Build and run the models and transformations that move a client's data through the onboarding stages of the pipeline, using SQL, Python, DBT, and Airflow.
Document each client's onboarding: data sources, decisions made, and any exceptions, contributing to shared onboarding procedures and templates.
Track onboarding progress and time, and surface areas of friction to improve the process so that it becomes faster and more repeatable over time.
Work with the broader Data Engineering team to research, learn, and implement new improvements to the onboarding pipeline’s efficiency & scalability so it can grow with us.
Qualifications and Experience
Education
Bachelor's degree in computer science, information systems, data science, or a related field is required. OR, equivalent practical experience is required, at least two years.
Experience Required
Suitable for a new or recent graduate; no prior professional experience required. Internships, academic projects, or other hands-on data work are a plus, as is a demonstrated ability to learn quickly.
Working proficiency in SQL and Python for data manipulation and analysis.
Some past experience working with and cleaning raw datasets.
Strong customer-service orientation and the ability to communicate clearly with non-technical clients.
Attention to detail, particularly around data quality, validation, and documentation.
Consistently takes initiative to learn and try new things, and keeps a mindset of constant improvement.
Experience Preferred
Exposure to Redshift, Snowflake, PostgreSQL, or similar databases.
Experience with Pandas DataFrames, Jupyter notebooks, and other quick data processing tools.
Familiarity with DBT, Airflow, or other data pipeline and orchestration tooling.
Familiarity with AWS S3 and Lambda functions, or other AWS services.
Experience working with Github, or another code version control platform.
Experience handling sensitive or confidential data and following security best practices.
Experience working in a startup, nonprofit, or mission-driven environment.
Skills Required
SQL
Python
Data cleaning & manipulation
Interpersonal skills
About CredLens
Non-degree credentials are reshaping how people move from learning to earning. Millions of learners are pursuing certificates, bootcamps, and workforce programs as pathways to better jobs and higher wages. But growth has outpaced clarity.
Thousands of offerings, uneven definitions, and fragmented outcomes data make it nearly impossible to distinguish impact from activity. When results are unclear, learners carry the risk, strong programs can't stand out, and investment can't reliably flow to what works.
CredLens exists to fix that.
We are a neutral, trusted source of high-quality outcomes data for non-degree credentials — connecting issuer-verified credential records to real-world employment, earnings, and education outcomes. Our partners use that data to improve programs, guide investment, and strengthen career pathways for learners.
Two years in, we have a firmly established platform, a growing client base, and the backing of Strada Education Foundation. We are not a startup finding its footing. We are a company beginning to scale — and we are building the team that will take us there.
Mission and Value Alignment
Travel Requirements
Approximately 5% domestic travel anticipated.
plus annual bonus
See All 342+ Data Center Operations Jobs in District of Columbia
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Find Data Center Operations JobsData Center Operations Jobs by City in District of Columbia
Where District of Columbia roles are concentrated, by current openings.
Data Center Operations Job Market in District of Columbia
A snapshot from current District of Columbia openings, updated as new roles post.
Who's Hiring
- Booz Allen Hamilton23
- Guidehouse11
- Meta10
- Parsons8
- CACI International8
Top Industries Hiring
- Technology & Software29
- Consulting & Professional Services14
- Education3
- Non-Profit & Social Services3
- Insurance2
What District of Columbia Employers Look For
The qualifications that appear most often in data center operations jobs across District of Columbia.
- Active CompTIA Security+ or equivalent certification recognized by federal contract employers
- Experience operating and maintaining physical data center hardware and cooling systems
- Familiarity with DCIM tools and real-time infrastructure monitoring platforms
- Ability to obtain and maintain a federal security clearance at Secret level or above
- Knowledge of network cabling standards, patch management, and structured wiring practices
- Experience with ticketing systems and change management processes in a 24/7 environment
Data Center Operations Jobs in District of Columbia: Frequently Asked Questions
How do you become a data center operations in District of Columbia?
The most direct path into data center operations in D.C. is completing an associate degree or technical certificate in information technology, computer networking, or systems administration, then earning vendor-neutral credentials such as CompTIA A+ and CompTIA Network+. Because a large share of D.C.-area data center roles sit inside federal contractor environments, candidates who pursue a security clearance early and add CompTIA Security+ gain a meaningful edge over those without it.
Which companies hire data center operationss in District of Columbia?
Companies currently hiring data center operationss in District of Columbia include Booz Allen Hamilton, Guidehouse, and Meta, per current listings on Migrate Mate as of July 2026. The D.C. market is particularly concentrated among defense IT contractors and federal civilian agency support contractors, so most large-scale hiring flows through established government services firms with long-term agency contracts.
Which District of Columbia cities have the most data center operations jobs?
The cities with the most data center operations openings in District of Columbia are Washington, District of Columbia, and Anacostia. Washington D.C. itself drives the largest share of postings because of the concentration of federal agencies, defense contractors, and telecommunications infrastructure that require staffed operations centers, while any adjacent suburban clusters reflect the dense campus footprints of major federal IT contractors operating near government client sites.
Are there remote data center operations jobs in District of Columbia?
Yes, but they're rare. Data center operations work is largely hands-on and requires physical presence for hardware maintenance, cabling, and equipment monitoring, so fully remote roles make up a small portion of the market. About 63% of data center operations openings tied to District of Columbia are remote or hybrid as of July 2026, and those tend to be monitoring, NOC analyst, or supervisory roles rather than floor-level technician positions.
How can I get hired as a data center operations in District of Columbia with little or no experience?
The most realistic entry path in D.C. is applying for help desk or IT support associate roles at federal contractors such as Leidos, SAIC, or Peraton, which regularly hire candidates at the junior level and provide on-the-job training toward data center responsibilities. Completing CompTIA A+ before applying, and beginning the security clearance process through any entry-level contractor role, positions candidates for internal moves into operations technician positions faster than external applications alone.
Where can I find and apply to data center operations jobs in District of Columbia?
You can find and apply to data center operations jobs in District of Columbia on Migrate Mate, which lists current D.C. openings updated regularly. Search the listings for roles that match your experience level and specialization, then apply directly to the ones that fit.
See All 342+ Data Center Operations Jobs in District of Columbia
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