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Financial Engineer Jobs in Virginia (NOW HIRING)

Senior Financial Software Engineer

Reston, VA · On-site

$127K - $168K/yr

MDAEdge is a company that focuses on delivering financial software solutions, and they are seeking a Senior Financial Software Engineer. In this role, you will be responsible for determining customer ...

UI/UX DEVELOPER

Mclean, VA · On-site

$50.75 - $66/hr

W2 Client's Financial Engineering team is seeking Developer-UX User Interface Senior for a large strategic financial project. The position is focused on UI/UX development for a software application ...

Showing results 21-40

Financial Engineer information

See Virginia salary details

$75.3K

$109.9K

$134.8K

How much do financial engineer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for financial engineer in Virginia is $109,862.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,100.00 and $123,400.00 per year, depending on experience, location, and employer.

What is a financial engineer?

A financial engineer, also called a computational engineer, advises clients on investment strategies and risk management based on quantitative analysis of their portfolio and the atmosphere in the stock market. As a financial engineer, your job duties include analyzing the stock market to predict how stocks will perform, building models of trends in the stock market based on market history, and make recommendations on how to manage their portfolio.

What is a financial engineer?

A Financial Engineer is a professional who applies mathematical techniques, computational tools, and financial theory to solve complex problems in finance. They are often involved in designing financial products, developing risk management strategies, and building quantitative models for pricing, trading, and portfolio management. Financial Engineers typically work for banks, investment firms, or financial technology companies, and their expertise is essential for managing financial risks and innovating new financial instruments.

What skills should a financial engineer have?

To thrive as a Financial Engineer, you need a strong background in mathematics, statistics, finance, and programming, typically supported by a degree in quantitative fields such as finance, mathematics, engineering, or computer science. Familiarity with technical tools like Python, R, MATLAB, financial modeling software, and sometimes certifications like CFA or FRM is highly valued. Exceptional problem-solving, analytical thinking, and the ability to communicate complex concepts clearly are vital soft skills. These skills and qualifications are crucial for designing innovative financial models, managing risks, and enabling data-driven decision-making in complex financial environments.

What are some common challenges financial engineers face when developing quantitative models, and how can they address them?

Financial Engineers often encounter challenges such as ensuring model accuracy, dealing with incomplete or noisy data, and adapting models to rapidly changing market conditions. Addressing these issues typically requires strong collaboration with data scientists, risk managers, and traders to validate assumptions and stress-test models under various scenarios. Staying current with industry trends and regulatory requirements also helps Financial Engineers maintain robust, compliant solutions that add value to their organizations.

What is the difference between Financial Engineer vs Quantitative Analyst?

AspectFinancial EngineerQuantitative Analyst
Required CredentialsDegree in finance, mathematics, or engineering; often CFA or FRM certificationsDegree in finance, mathematics, or statistics; often CFA or FRM certifications
Work EnvironmentFinancial institutions, hedge funds, investment banksAsset management firms, hedge funds, investment banks
Job FocusDeveloping complex financial models, derivatives pricing, risk managementData analysis, model development, trading strategies
Common UsageDesigning financial products and strategiesAnalyzing data to inform trading decisions

Financial Engineers and Quantitative Analysts share similar educational backgrounds and certifications, often working in similar environments like investment banks and hedge funds. While Financial Engineers focus on creating complex financial models and derivatives, Quantitative Analysts primarily analyze data to support trading strategies. Both roles require strong quantitative skills and contribute to financial innovation and risk management.

Do financial engineers make a lot of money?

Financial engineers often earn high salaries due to their specialized skills in quantitative analysis, modeling, and programming. Compensation varies based on experience, location, and industry, but many financial engineers have the potential to earn six-figure incomes or more, especially with advanced degrees and certifications like the CFA or FRM.

How much do financial engineers make?

Financial engineers in general earn a median annual salary of around $100,000 to $130,000, with experienced professionals and those working in major financial centers earning higher. Salaries can vary based on experience, education, certifications like CFA or FRM, and the complexity of financial models used. Entry-level positions typically start lower, while senior roles can exceed $200,000 annually.

What are the most commonly searched types of Financial Engineer jobs in Virginia?

The most popular types of Financial Engineer jobs in Virginia are:

What cities in Virginia are hiring for Financial Engineer jobs?

Cities in Virginia with the most Financial Engineer job openings:

Infographic showing various Financial Engineer job openings in Virginia as of September 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 3% Contract, and 1% Nights. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $109,862 per year, or $52.8 per hour.

Data Engineer

Reston, VA • On-site

$119K - $143K/yr

Full-time

Posted 25 days ago


Key responsibilities

  • Design and implement data ingestion, integration, and transformation solutions that consolidate enterprise data from multiple sources.

  • Develop and implement data pipelines to cleanse, standardize, validate, and enrich data to ensure data accuracy, consistency, and fitness for downstream use.

  • Monitor ETL/ELT data pipeline health and data quality metrics through observability and quality tools, taking proactive steps to address data quality issues before they impact downstream consumers.


Job description

FEDERAL HOME LOAN BANKS OFFICE OF FINANCE 

POSITION DESCRIPTION

POSITION: Data Engineer                                                          DATE: August 2026

       DEPARTMENT: Information Technology                                 FLSA: Exempt

       REPORTS TO: Senior Manager, Data & Platform Engineering


SUMMARY OF POSITION

The Data Engineer will serve as the Office of Finance’s subject matter expert on a multitude of data engineering methods, data integration and data management technologies. This is a highly technical role responsible for leading the data engineering lifecycle across the organization’s data planes — from raw data ingestion through data cleansing, data standardization, data transformation, data modeling, and data delivery. The scope of the role spans data integration with on-premises source systems through cloud-based data processing, data storing, and works in tandem with other teams who support data serving and data delivery layers.

The Data Engineer works collaboratively across internal data stakeholders and data consumers to identify, prove and implement opportunities to improve data discovery, data collection, data transformation, data standardization, data storage, and data quality. The Data Engineer assists data stakeholders in maintaining an enterprise view of the organization’s data assets, and works with Product Owners/Leaders to consider opportunities to enhance both the organization and the FHLBanks System at large via compelling data products.

We’re proud of the way our teammates have a positive impact on everything we do. Our employees are committed to and exemplify our Core Values:

  • Integritythrough accountability, consistency,transparencyand trust
  • Agilitythrough adaptability, continuous improvement,expertise, and flexibility
  • Partnershipthrough collaboration, communication, leadership, and teamwork
  • Inclusivitythrough diversity, relationships, respect, and support

PRINCIPAL RESPONSIBILITIES

  • Design and implement data ingestion, integration, and transformation solutions thatconsolidateenterprise data from multiple sources.
  • Develop and implement data pipelines to cleanse, standardize,validateand enrich data to ensure data accuracy, consistency, and fitness for downstream use.
  • Apply data profiling and statistical analysis techniques to characterize data distributions,identifyanomalies, detect structural problems, and support overall data quality.
  • Implement and automate data quality controls andmonitoringtoidentify, prevent, and remediate data issues throughout the data lifecycle.
  • Build dimensional models, fact tables, and semantic layers that support downstream analytics and reusability of business data.
  • Assistdata stakeholders in documenting data assets including lineage, data dictionaries, and ownership through the enterprise data catalog.
  • Monitor ETL/ELT data pipeline health and data quality metrics through observability and quality tools, taking proactive steps to address data quality issues before theyimpactdownstream consumers.
  • Participate in on-call rotation as needed for support of data products and pipelines.
  • Assistwith other job duties as assigned.

PRINCIPAL REQUIREMENTS

  • Bachelor’s degree inComputer Science,Statistics, Mathematics, Finance, Financial Engineering, Quantitative Finance, Information Science, Data Engineering, or a related quantitative field. Master’s degree or above preferred.A combination of advanced education anddirectly relatedexperience may be combinedtodemonstratedsubject matterexpertise, provided education is a graduate or terminal degree.
  • Subject matterexpertisein the following areas:
  • At least 5-7 years of data engineering experience withdemonstratedownership of Production data pipelines.
  • At least 5-7 yearsdemonstratedexperience in applied exploratory data analysis, descriptive statistical analysis, and inferential statistical analysis in the development and delivery of enterprise data products and data visualizations.
  • At least 3-5 years of hands-on experience with ETL/ELT including job design, dataflow optimization, and integration.
  • At least 3-5 years of experience with industry leading analytical data platforms, (e.g., Azure Data Factory, Synapse, Databricks, Azure Data Lake Storage, Delta Lake, Spark SQL, and Unity Catalog, or other comparable Azure cloud data services.)
  • Prior experience in financial services, capital markets, or government sponsored entities strongly preferred.
  • Technical skills:
  • Programming/Scripting: Python (pandas,PySpark, SQL Alchemy or other similar data engineering scripting tooling), SQL (proficient), Bash (optional)
  • Data Integration: Azure Data Factory, Azure SynapsePipelinesor other comparable tooling
  • Storage: Azure Data Lake Storage or comparable, PostgreSQL (Familiar), SAP ASE (Optional)
  • Analytics Engineering: Azure Synapse Analytics, Delta Live Tables, Apache Spark, or other comparable tooling
  • BI/Reporting: Power BI (proficient), SAP BusinessObjects (optional)
  • DevOps: GitHub Enterprise, CI/CD pipelines
  • Data Governance: Microsoft Purview or comparable, Data lineage, cataloging, access control
  • Observability: Datadog, Grafana, Prometheus, or comparable tooling
  • Ability to develop and refine an evolving understanding of business requirements and needs.
  • Ability to rapidly iterate upon ideas as on-going mechanism to progressivelyvalidatebusiness value and seek clarity in desired business outcomes.
  • Ability to communicate well, both orally and in writing, including producing thorough documentation of all work.
  • Ability to conduct independent technical research and share results with management and/or peers.
  • Ability to listen and integrate ideas from different views, build andmaintainrespectful relationships, collaborate with others, and resolve conflicts constructively.
  • Proof of eligibility to work in the United States.

This position has an annualized salary range of $138,375 - $212,218. The final salary offered within this range is dependent on various factors, including but not limited to the responsibilities of the position, the experience, skill set and other relevant qualifications of the applicant and internal pay equity.


EQUAL EMPLOYMENT OPPORTUNITY: 

The Federal Home Loan Banks Office of Finance is committed to equal employment opportunity without regard to race (including traits historically associated with race, such as hair texture, hair type and protective hairstyles), color, religion, sex, pregnancy (including childbirth, lactation, and related medical conditions), national origin or ancestry, ethnic origin, age, physical or mental disability, veteran status, uniformed service member status, military status, sexual orientation, gender identity, status as a parent, marital status, genetic information (including testing and characteristics), citizenship or immigration status, or any other characteristic protected by applicable federal, state, or local law.