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Data Engineer Finance Jobs in Reston, VA (NOW HIRING)

Anika Systems

Data Engineer

Leesburg, VA · On-site +1

$115K - $139K/yr

XBRL & Financial Data Processing * Develop pipelines to ingest, parse, and normalize XBRL ... Context Engineering & Data Modeling Support * Apply context engineering principles to ensure data ...

ProSidian Consulting

Data Engineer

Alexandria, VA · Hybrid

$122K - $147K/yr

ProSidian.com ProSidian Seeks a Data Engineer | Workforce Planning & Strategic Human Capital ... Skills Required Primarily focused on Management and Financial Consulting, Acquisition and Grants ...

ProSidian Consulting, LLC

Data Engineer

Alexandria, VA · Hybrid

$122K - $147K/yr

ProSidian.com ProSidian Seeks a Data Engineer | Workforce Planning & Strategic Human Capital ... Skills Required Primarily focused on Management and Financial Consulting, Acquisition and Grants ...

Carlyle

Data Engineer

Washington, DC · On-site

$160K - $200K/yr

Data Engineer Location: Washington, DC Line of Business: Data Science Job Function: Investor ... The role demands expertise in Python, deep familiarity with financial data sources, and the ability ...

Cornerstone Defense

Data Engineer

Chantilly, VA · On-site

$117K - $140K/yr

Life Planning Financial & Legal Services * Develop new tools, code, and services to execute data engineering activities involving data of varying types and in varying conditions. Activities include ...

Booz Allen Hamilton, Inc.

Data Engineer

Chantilly, VA · On-site

$77K - $176K/yr

Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Info Gain Consulting

Data Engineer

Alexandria, VA · On-site +1

$122K - $147K/yr

We deliver program management, financial management, performance improvement, and technology ... Position Overview: We are seeking a skilled Data Engineer to join our team, supporting the ...

Info Gain Consulting

Data Engineer

Alexandria, VA · Remote

$122K - $147K/yr

We deliver program management, financial management, performance improvement, and technology ... Position Overview: We are seeking a skilled Data Engineer to join our team, supporting the ...

Booz Allen Hamilton

Data Engineer

Arlington, VA · On-site

$62K - $141K/yr

As a data engineer, you know that organizing data can yield pivotal insights when it's gathered ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

BOOZ, ALLEN & HAMILTON, INC.

Data Engineer

Arlington, VA

$62K - $141K/yr

Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Booz Allen Hamilton

Data Engineer

Chantilly, VA · On-site

$77K - $176K/yr

Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Booz Allen Hamilton, Inc.

Data Engineer

Arlington, VA · On-site

$62K - $141K/yr

Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

BOOZ, ALLEN & HAMILTON, INC.

Data Engineer

Arlington, VA

$62K - $141K/yr

Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Booz Allen Hamilton, Inc.

Data Engineer

Arlington, VA · On-site

$62K - $141K/yr

Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Booz Allen Hamilton

Data Engineer

Arlington, VA · On-site

$62K - $141K/yr

Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Booz Allen Hamilton, Inc.

Data Engineer

Chantilly, VA · On-site

$77K - $176K/yr

Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Booz Allen Hamilton, Inc.

Data Engineer

Arlington, VA · On-site

$62K - $141K/yr

Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Booz Allen Hamilton

Data Engineer

Arlington, VA · On-site

$62K - $141K/yr

Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Booz Allen Hamilton

Data Engineer

Arlington, VA · On-site

$62K - $141K/yr

R0237363 Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

Booz Allen Hamilton

Data Engineer

Chantilly, VA · On-site

$77K - $176K/yr

R0241347 Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and ... Our offerings include health, life, disability, financial, and retirement benefits, as well as paid ...

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Showing results 1-20

All JobsData Engineer Finance JobsData Engineer Finance Jobs in Reston, VA

Data Engineer Finance information

See Reston, VA salary details

$46.3K

$135K

$184.7K

How much do data engineer finance jobs pay per year?

As of Jun 9, 2026, the average yearly pay for data engineer finance in Reston, VA is $134,951.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,100.00 and $143,000.00 per year, depending on experience, location, and employer.

What does a Data Engineer in Finance do?

A Data Engineer in Finance is responsible for designing, building, and maintaining data pipelines and architectures that support the collection, storage, and analysis of financial data. They ensure that financial institutions have reliable access to accurate and timely data for analytics, reporting, and regulatory compliance. Their work often involves integrating data from multiple sources, optimizing data workflows, and collaborating with data scientists and analysts to deliver actionable insights. Data Engineers in Finance play a crucial role in enabling data-driven decision-making while ensuring data security and integrity.

How does a Data Engineer in Finance typically collaborate with analysts and other stakeholders to ensure data reliability and compliance?

Data Engineers in Finance work closely with data analysts, business intelligence teams, and compliance officers to design pipelines that deliver accurate, timely, and compliant data. Regular communication is essential to understand reporting requirements, data quality standards, and regulatory constraints. They often participate in cross-functional meetings to prioritize tasks, resolve data discrepancies, and implement controls that meet both business and legal needs. This collaboration ensures that data products not only support decision-making but also adhere to financial industry regulations.

What is the difference between Data Engineer Finance vs Data Analyst Finance?

AspectData Engineer FinanceData Analyst Finance
Primary RoleBuilds and maintains data pipelines, infrastructure, and databases for financial dataAnalyzes financial data to generate reports and insights
Skills & CertificationsSQL, Python, ETL tools, cloud platforms, data modelingExcel, SQL, data visualization tools, basic scripting
Work EnvironmentData engineering teams, IT departments, cloud environmentsFinance teams, business units, reporting platforms
Industry UsageUsed across financial institutions for data infrastructureUsed for financial reporting and decision-making

Data Engineer Finance focuses on creating and managing the data infrastructure necessary for financial data processing, while Data Analyst Finance interprets this data to provide actionable insights. Both roles are essential in financial organizations but serve different functions within the data ecosystem.

What are the key skills and qualifications needed to thrive as a Data Engineer in Finance, and why are they important?

To thrive as a Data Engineer in Finance, you need expertise in data modeling, ETL processes, and a strong foundation in SQL, Python, or Scala, often supported by a degree in computer science, information systems, or a related field. Familiarity with financial data platforms, cloud services (like AWS or Azure), and tools such as Apache Spark, Hadoop, and relevant data security certifications is common. Collaboration, attention to detail, and strong problem-solving skills are standout soft skills for this role. These abilities ensure reliable data pipelines, compliance with financial regulations, and actionable insights that support critical business decisions.
What are popular job titles related to Data Engineer Finance jobs in Reston, VA? For Data Engineer Finance jobs in Reston, VA, the most frequently searched job titles are:
What job categories do people searching Data Engineer Finance jobs in Reston, VA look for? The top searched job categories for Data Engineer Finance jobs in Reston, VA are:
What cities near Reston, VA are hiring for Data Engineer Finance jobs? Cities near Reston, VA with the most Data Engineer Finance job openings:
Data Engineer Finance jobs near you
Infographic showing various Data Engineer Finance job openings in Reston, VA as of June 2026, with employment types broken down into 87% Full Time, 3% Part Time, and 10% Contract. Highlights an 77% In-person, 13% Hybrid, and 10% Remote job distribution, with an average salary of $134,951 per year, or $64.9 per hour.
Data Engineer

Data Engineer

Anika Systems

Leesburg, VA • On-site, Remote

$115K - $139K/yr

Full-time

Posted 17 days ago

Job description

Anika Systems is seeking a skilled Data Engineer to design, build, and optimize scalable data pipelines and platforms supporting federal clients. This role will play a critical part in enabling enterprise data strategies, supporting Office of the Chief Data Officer (OCDO) initiatives, and delivering high-quality, trusted data for analytics, reporting, and mission operations.
This opportunity is 100% remote.
The ideal candidate has hands-on experience with ETL/ELT pipelines, XBRL data processing, Apache Iceberg-based architectures, and advanced data optimization techniques such as materialized views and context-aware data engineering. This role also requires proficiency in AI tools and AI-assisted development workflows, along with experience building and deploying CI/CD pipelines for data and analytics platforms.
Key Responsibilities
Data Pipeline Development & ETL/ELT
  • Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data across enterprise platforms.
  • Build scalable data ingestion frameworks for structured and semi-structured data, including XBRL filings and financial datasets.
  • Implement data transformation logic to support analytics, reporting, and regulatory use cases.
  • Ensure data pipelines are reliable, performant, and scalable in cloud environments.
  • Leverage AI-assisted development tools to accelerate pipeline development, testing, and optimization.
Cloud Data Platforms & Iceberg Architecture
  • Develop and manage data solutions leveraging AWS services (e.g., S3, Airflow, DAGs, Glue, Lambda, Redshift).
  • Implement and optimize Apache Iceberg table formats for large-scale, ACID-compliant data lakes.
  • Support lakehouse architectures that unify data lakes and data warehouses.
  • Optimize data storage and retrieval strategies for performance and cost efficiency.
  • Enable data platforms that support AI/ML workloads and downstream generative AI use cases.
CI/CD & DataOps Engineering
  • Design and implement CI/CD pipelines for data pipelines, infrastructure, and analytics code using tools such as GitHub Actions, GitLab CI, Jenkins, or AWS-native services.
  • Automate build, test, and deployment processes for ETL pipelines and data platform components.
  • Implement DataOps best practices, including version control, automated testing, environment promotion, and rollback strategies.
  • Ensure reproducibility, reliability, and governance of data pipeline deployments across environments.
  • Integrate AI-driven testing and monitoring tools to improve pipeline quality and reduce operational risk.
Data Optimization & Performance Engineering
  • Design and implement materialized views and other performance optimization techniques to improve query efficiency.
  • Tune data pipelines and queries for performance, scalability, and cost.
  • Implement partitioning, indexing, and caching strategies aligned to workload patterns.
XBRL & Financial Data Processing
  • Develop pipelines to ingest, parse, and normalize XBRL (eXtensible Business Reporting Language) data.
  • Support regulatory and financial data use cases requiring high accuracy and traceability.
  • Ensure alignment with data standards and validation rules for financial reporting datasets.
Context Engineering & Data Modeling Support
  • Apply context engineering principles to ensure data is enriched with meaningful metadata, lineage, and business context.
  • Collaborate with Data Architects to support data modeling, schema design, and entity relationships.
  • Enable downstream analytics and AI use cases by structuring data for usability, discoverability, and governance.
Metadata, Data Catalog, and Governance Integration
  • Integrate pipelines with enterprise data catalogs and metadata management systems.
  • Support automated metadata capture, lineage tracking, and data quality monitoring.
  • Ensure alignment with data governance frameworks and standards established by OCDO organizations, including AI data readiness and traceability.
Stakeholder Collaboration & Agile Delivery
  • Collaborate with data architects, analysts, and business stakeholders to understand data needs and deliver solutions.
  • Participate in stakeholder listening campaigns, workshops, and data discovery efforts.
  • Work in Agile teams to iteratively deliver data capabilities and enhancements.
  • Contribute to identifying and implementing AI-driven efficiencies and automation opportunities across the data lifecycle.
Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
  • 5+ years of experience in data engineering, ETL development, or data platform engineering.
  • Strong hands-on experience with:
    • ETL/ELT tools and frameworks
    • AWS data services (S3, Glue, Lambda, Redshift, etc.)
    • Apache Iceberg and modern data lake architectures
  • Experience designing and implementing CI/CD pipelines for data platforms and ETL workflows.
  • Demonstrated proficiency using AI tools and AI-assisted development workflows (e.g., LLM copilots, automated code generation, pipeline optimization tools).
  • Experience processing XBRL or complex financial/regulatory datasets.
  • Proficiency in SQL and Python.
  • Experience implementing materialized views and query optimization techniques.
  • Understanding of data modeling concepts and metadata management.
  • Familiarity with data governance, data quality practices, and data readiness for AI/ML use cases.
  • Ability to work in Agile, DevOps-oriented environments.
  • U.S. Citizenship required; ability to obtain and maintain a federal clearance.
Preferred Qualifications
  • Experience supporting federal agencies such as SEC, DHS, Treasury, or Federal Reserve System.
  • Familiarity with data catalog tools (e.g., Collibra, Alation, ServiceNow).
  • Experience with Apache Spark, Kafka, or other distributed data processing frameworks.
  • Experience enabling data pipelines for AI/ML or generative AI applications.
  • Knowledge of data maturity frameworks (e.g., EDM DCAM, TDWI).
  • Exposure to context engineering or semantic data layer design.
  • AWS or data engineering certifications.
  • Experience with infrastructure-as-code (IaC) tools (e.g., Terraform, CloudFormation) in support of CI/CD pipelines.

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