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Overnight Data Analytics Engineer Jobs in Washington, DC

SES

Data Analytics Engineer

Reston, VA · On-site

$119K - $143K/yr

Systems Engineering Services is seeking a Data Analytics Engineer based out of the Reston-DMV area. This position will require hybrid work in office in the Reston Town Center. Top 5 Technical Skills:

Ryde Technologies, LLC

Data Analytics Engineer

Arlington, VA · On-site

$130K - $157K/yr

Job Overview We are seeking a Data Analytics Engineer to support our Federal Government Customer with delivering secure, cloud-based mission systems. The Engineer will contribute to the design ...

CGI Inc.

Senior Data Analytics Engineer

Reston, VA · On-site

Senior Data Analytics Engineer Category: Business Analysis (functional and technical) Main location: United States, Virginia, Reston Position ID:J0726-0947 Employment Type: Full Time U.S. - Finding ...

@Orchard

Lead Data Analytics Engineer

Washington, DC · Remote

$160K - $230K/yr

Lead Data Analytics Engineer Remote/Work from Home within the United States Must be a U.S. Citizen with an active or interim Secret Clearance. @Orchard LLC has an immediate need for a Lead Analytics ...

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All JobsData Analytics Engineer JobsOvernight Data Analytics Engineer JobsOvernight Data Analytics Engineer Jobs in Washington, DC

Overnight Data Analytics Engineer information

See Washington, DC salary details

$50.4K

$146.9K

$201K

How much do overnight data analytics engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for overnight data analytics engineer in Washington, DC is $146,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,700.00 and $155,700.00 per year, depending on experience, location, and employer.

What is the difference between Overnight Data Analytics Engineer vs Data Analyst?

AspectOvernight Data Analytics EngineerData Analyst
CredentialsBachelor's in Data Science, Computer Science, or related field; experience with data engineering toolsBachelor's in Statistics, Mathematics, or related field; proficiency in data visualization and analysis tools
Work EnvironmentData engineering teams, often in 24/7 operations, focusing on data pipeline maintenanceBusiness or analytics teams, typically during regular business hours, focusing on data interpretation
Employer & Industry UsageTech companies, financial institutions, healthcare, requiring overnight data processingMarketing firms, retail, consulting, focusing on data reporting and insights

The Overnight Data Analytics Engineer primarily handles data pipeline development and maintenance during overnight shifts, often requiring technical skills in data engineering. In contrast, Data Analysts focus on interpreting data, creating reports, and providing insights during regular hours. Both roles are essential but differ in technical scope and work hours.

What are the most commonly searched types of Data Analytics Engineer jobs in Washington, DC?

The most popular types of Data Analytics Engineer jobs in Washington, DC are:

Overnight Data Analytics Engineer jobs near you

Data Analytics Engineer

SES

Reston, VA • On-site

$119K - $143K/yr

Other

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

Systems Engineering Services is seeking a Data Analytics Engineer based out of the Reston-DMV area. This position will require hybrid work in office in the Reston Town Center.

Top 5 Technical Skills:

  1. Python
  2. SQL
  3. API /. SDLC
  4. Data Insights and Visualization
  5. Financial Services Domain Knowledge

Job Description:

Seeking an experienced Data Analytics Engineer / Business UAT Tester with 7+ years of analytics, monitoring, visualization, production support, and developer collaboration experience, including 5+ years validating business requirements, data outputs, reports, APIs, and applications before production deployment. Hands-on with GenAI-assisted data extraction, prompt-guided validation, report-ready JSON generation, summarization, trend analysis, anomaly detection support, and validation of generated narratives, tables, and charts. Provides white glove user onboarding and embedded, forward-deployed style support to help developers, QA, analytics teams, and business users operationalize GenAI-enabled reporting solutions in regulated enterprise environments.

  • Business UAT & production readiness: Plan, execute, and document UAT test cases, expected results, evidence, defects, regression validation, acceptance criteria, requirements traceability, user sign-off, and release-readiness decisions.
  • GenAI-enabled ingestion and reporting: Support developers and business teams in designing, testing, and validating dynamic data ingestion and report generation workflows, including source-to-report reconciliation and business-ready outputs.
  • GenAI output validation: Validate extracted data, nested JSON payloads, generated summaries, trend insights, anomaly detection outputs, and narrative, table, and chart results using human-in-the-loop review and business-rule checks.
  • JSON/API and data quality validation: Validate REST API request/response payloads, nested JSON, schema alignment, metadata completeness, SQL reconciliation, source-to-output accuracy, and Jira-supported defect resolution using Postman and Swagger/OpenAPI.
  • Forward-deployed stakeholder support: Work closely with business users, product owners, developers, QA, model risk, validation, analytics, and technology teams to clarify requirements, resolve rollout issues, and close feedback loops during delivery.
  • White glove onboarding and adoption: Create onboarding guides, SOPs, user guides, training materials, UAT artifacts, knowledge-transfer content, and adoption playbooks; facilitate walkthroughs, answer user questions, capture feedback, and coordinate early-life support.

Technical Skills

GenAI Skills: Prompt-assisted extraction, field/entity mapping, GenAI output validation, report-ready JSON generation, summarization, trend analysis support, anomaly detection review, exception handling, human-in-the-loop quality checks, and validation of generated narratives, tables, and charts.

SQL / Databases: Strong SQL for complex analytical queries, source-to-target validation, reconciliation, semi-structured data analysis, data quality checks, production-readiness testing, relational database concepts, and use of SQL workbench/query tools for testing and validation.

Python: pandas, NumPy, JSON parsing/transformation, dynamic ingestion support, report generation workflows, analytics automation, and pipeline testing.

JSON / APIs: REST APIs, request/response payloads, nested JSON, Postman, Swagger/OpenAPI, schema checks, metadata validation, and API testing.

Tools / Methods: Jira, Agile/Scrum methodologies, AWS cloud platforms, dashboards, visualization, model monitoring, documentation tools, developer collaboration, white glove onboarding, and forward-deployed enablement.

Experience & Qualifications

Experience: 7+ years of software development, analytics, data engineering, monitoring, visualization, production support, dynamic ingestion support, report-generation testing, and business enablement experience.

Business UAT: 5+ years validating requirements, test cases, defects, fixes, regression outcomes, generated reports, data outputs, user adoption needs, and production readiness with stakeholders and developers.

Regulated delivery: Financial services or regulated enterprise experience, including documentation, validation, model risk, analytics, governance reporting, stakeholder engagement, and enterprise delivery standards.

Education

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Engineering or a related quantitative field.

Jake Lutman

Techncial Recruiter

Systems Engineering Services

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