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Financial Data Engineer Remote Jobs in Virginia (NOW HIRING)

BDR Solutions LLC

Data Engineer - Senior

Herndon, VA · On-site +1

$110K - $170K/yr

BDR Solutions is seeking a seasoned Cloud Data Engineering Lead to support IRS data platform ... Contribute to tenant onboarding automation, financial operations integration, and ROI reporting

rockITdata

Full Stack Data Engineer

Arlington, VA · On-site +1

This is a Remote position. Key Responsibilities * Data Ingestion and Integration: * Design and ... Integrate data engineering workflows with existing software systems and platforms. * Monitoring and ...

A-TEK Inc.

Health IT Data Engineer

Alexandria, VA · Remote

$125K - $135K/yr

The Health IT Data Engineer will design, build, integrate, and optimize enterprise data pipelines ... This is a remote position requiring all work be performed in the continental United States. US ...

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Financial Data Engineer Remote information

What does a financial data engineer do in a remote role?

A Financial Data Engineer designs, builds, and maintains systems that process and analyze large sets of financial data. Working remotely, they collaborate with teams to develop data pipelines, integrate financial databases, and ensure the reliability of data used for financial analysis and reporting. They often use programming languages like Python or SQL, and work with big data tools to support data-driven decision-making for financial institutions or fintech companies. Their work is crucial to transforming raw financial data into actionable insights.

What are the key skills and qualifications needed to thrive as a financial data engineer in a remote role?

To thrive as a Financial Data Engineer (Remote), you need strong programming skills (such as Python or SQL), experience with data modeling, and a background in finance or quantitative analysis, often supported by a relevant degree. Proficiency with big data platforms (like Hadoop or Spark), ETL tools, and cloud data services (such as AWS or Azure) is typically required, alongside certifications in data engineering or finance. Excellent problem-solving, communication, and time management skills help you collaborate effectively and independently in a distributed environment. These capabilities are crucial for building reliable financial data pipelines, ensuring data quality, and supporting timely, data-driven business decisions.

What are the typical challenges faced by remote financial data engineers when collaborating with cross-functional teams?

Remote Financial Data Engineers often work closely with data analysts, software developers, and business stakeholders across different time zones. One common challenge is ensuring effective communication and alignment on project requirements, especially when dealing with complex financial data pipelines and evolving business needs. Utilizing collaborative tools, maintaining clear documentation, and participating in regular virtual meetings can help bridge gaps and foster productive teamwork. Staying proactive about updates and being responsive to feedback are key to ensuring smooth collaboration in a remote environment.

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

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

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For Financial Data Engineer Remote jobs in Virginia, the most frequently searched job titles are:

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The top searched job categories for Financial Data Engineer Remote jobs in Virginia are:

What cities in Virginia are hiring for Financial Data Engineer Remote jobs?

Cities in Virginia with the most Financial Data Engineer Remote job openings:

Financial Data Engineer Remote jobs near you

Data Platform Engineer, AI & Personalization (Remote, East Coast)

P3Hired

Arlington, VA • On-site, Remote

$131K - $158K/yr

Full-time

Re-posted 27 days ago

Job description

Position Overview
Eagle Eye is an AI driven retail technology SaaS company powering personalized promotions and loyalty programs for leading global brands. In this role, you will sit at the heart of our platform building, optimizing, and supporting data systems that deliver high performance, real time personalization for enterprise clients.
As a Data Solutions Engineer, you will play a key role in deploying, operating, and continuously improving our data-driven platform for our clients.
You will work at the intersection of data engineering, system performance optimization, and client-facing technical operations, ensuring that our AI personalization solution runs reliably in production and delivers measurable value.
You will collaborate closely with Product Managers, Data Science, and Customer Success teams, and regularly interact with client technical teams.
The team "Personalized Challenges" is currently Europe-based and you will be the first North America based member. You will primarily communicate remotely with your direct team members in Europe but will also collaborate with our extensive team in North America who are based in Washington, DC, Toronto, Jacksonville and Chicago. Note that overall, Eagle Eye has a global presence, including North America, EMEA and APAC.
This is a United States based remote role with a preference for Eastern time zone candidates, open to applicants authorized to work without sponsorship.
Responsibilities
This role is intentionally a hybrid of responsibilities:
  • Hands-on Data Engineering - 60%
  • Continuous Optimization of Data-Driven Systems - 30%
  • Client-facing Technical Support & Ticket Resolution - 10%

Success in this role is measured by platform reliability, data quality, system performance, and the long-term resolution of production issues, rather than by volume of support tickets.
Platform Deployment & Data Integration
  • Integrate client data pipelines into our data stack
  • Deploy and configure our platform for new clients
  • Ensure data quality, consistency, and reliability across incoming and outgoing data flows
Production Support & Ticket Management
  • Investigate and resolve technical tickets related to data pipelines, system performance, and algorithm behavior
  • Act as a technical escalation point for Customer Success teams
  • Diagnose root causes, propose fixes, and ensure long-term prevention of recurring issues
Continuous Optimization & Performance Improvement
  • Analyze system and algorithm performance using metrics, logs, and experimentation
  • Identify opportunities to optimize data pipelines, processing logic, and algorithm configurations
  • Collaborate with Product and Data Science teams to prioritize and roll out improvements
  • Design and analyze A/B tests to measure the impact of changes

You Are
  • Disciplined problem-solver who enjoys digging into the "why" of system behavior to find long-term solutions.
  • An autonomous worker, ready to be the first North American member of the team while maintaining effective collaboration with European colleagues.
  • A clear, structured communicator capable of explaining complex technical issues to both engineers and non-technical stakeholders.
  • Rigorous and detail-oriented, especially when monitoring production systems and ensuring data integrity.
  • Comfortable navigating production incidents and support tickets with a calm, engineering-driven approach.
  • Curious and pragmatic, motivated by understanding real-world client use cases and optimizing system performance.
  • Comfortable working fully remotely: even if located near other team members, you will be remote from your direct colleagues based in France. You have proven experience thriving in a fully remote setup and collaborating across cultures.
  • Able to participate in a 1-2 week onboarding in Paris, offering dedicated time for in-person collaboration, learning, and team connection.
You Have
  • 3-5 years of experience as a Data Engineer or Data Solutions Engineer in a production-heavy environment.
  • A bachelors degree in Computer Science, Data Engineering, or a related field.
  • Deep hands-on experience with Python and/or Scala.
  • Proven expertise using Spark for large-scale data processing.
  • Practical experience building and managing data stacks within Google Cloud Platform (GCP) and BigQuery.
  • A solid foundation in data engineering principles, including data pipeline design and system optimization.
  • A working knowledge of Data Science and Machine Learning concepts to help bridge the gap between data flows and algorithm performance.

Department Technology Locations Arlington, VA Client Name Eagle Eye

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