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Graduate Data Engineer Jobs in Virginia (NOW HIRING)

Mechanical Engineering Location: Blacksburg, Virginia Categories: Academic Advising / Support The ... Experience creating and analyzing surveys or qualitative data, and using survey instruments ...

Senior Data Scientist

Alexandria, VA · On-site

$180 - $260/hr

Collaborate with multidisciplinary teams of analysts, engineers, and developers to solve complex ... Bachelor's, Master's, or equivalent graduate degree in a quantitative or analytical field (Computer ...

AI Engineer

Alexandria, VA · On-site

$180 - $240/hr

... data engineering, platform engineering, cybersecurity, and observability in a fast‑paced, engineering‑centric environment Requirements * Bachelor's, Master's, or equivalent graduate degree in a ...

Graduate degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative discipline; academic research experience may be considered equivalent to industry ...

Senior Data Scientist

Alexandria, VA · Hybrid

$131K - $237K/yr

Contribute to the integration of AI, DevSecOps, data engineering, platform engineering ... What You Bring: * Bachelor's, Master's, or equivalent graduate degree in a quantitative or ...

... data engineering, platform engineering, cybersecurity, and observability in a fast‑paced, engineering‑centric environment. Requirements * Bachelor's, Master's, or equivalent graduate degree in a ...

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Graduate Data Engineer information

See Virginia salary details

$44.1K

$128.6K

$176K

How much do graduate data engineer jobs pay per year?

As of Aug 29, 2026, the average yearly pay for graduate data engineer in Virginia is $128,604.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,300.00 per year, depending on experience, location, and employer.

What is a graduate data engineer?

A Graduate Data Engineer is an entry-level role focused on designing, building, and maintaining data pipelines and infrastructure. They work with large datasets, ensuring data is collected, processed, and stored efficiently for analysis. Typically, they collaborate with data scientists, analysts, and other engineers to support data-driven decision-making. This role often involves using programming languages like Python or SQL, cloud platforms, and big data technologies. Graduate Data Engineers gain hands-on experience in data engineering principles and tools, helping organizations manage and optimize their data workflows.

What does a graduate data engineer do?

As a Graduate Data Engineer, your daily tasks may include building and maintaining data pipelines, assisting with data cleansing and transformation, and collaborating with data scientists and other engineers to deliver reliable datasets. You'll often work with structured and unstructured data, write scripts to automate data workflows, and help troubleshoot data integration issues as they arise. Throughout your work, you'll be expected to document processes and learn new tools or technologies as the team evolves. This role provides an excellent opportunity to develop hands-on technical skills while working closely with experienced professionals in a collaborative setting.

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

A Graduate Data Engineer typically requires a bachelor's degree in computer science, engineering, mathematics, or a related field, along with foundational knowledge of programming, data structures, and database concepts. Familiarity with technologies such as SQL, Python, cloud platforms (e.g., AWS, Azure), and modern data engineering tools like Apache Spark or Hadoop is often expected, and introductory certifications can provide an added advantage. Strong analytical thinking, problem-solving ability, effective communication, and eagerness to learn are valuable soft skills in this role. These skills and qualities are crucial for efficiently building, maintaining, and optimizing data pipelines that support business decision-making.

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

The most popular types of Graduate Data Engineer jobs in Virginia are:

Infographic showing various Graduate Data Engineer job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $128,604 per year, or $61.8 per hour.

Data Engineer

Reston, VA • On-site

$119K - $143K/yr

Full-time

Posted 9 days ago


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.