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Financial Data Engineer Remote Jobs in Houston, TX

Arva Intelligence

Data Engineer

Houston, TX · On-site +1

$95K - $130K/yr

Remote Base Salary Range: $95k - $130k General Position Description The Data Engineer is responsible for building and scaling the data and computational backbone that supports Arva's ecosystem ...

Metro National Corporation

Data Engineer

Houston, TX · On-site +1

$109K - $131K/yr

Remote candidates will not be considered. We do not Sponsor Visa's SUMMARY: MetroNational is ... We are seeking a skilled Data Visualization & Analytics Engineer to join our data management team.

NAVA Software Solutions

AI Engineer -Remote

Houston, TX · On-site +1

AI Engineer Location: 100% Remote Duration: 6+ month contract-to-hire Requirement: * Implemented ... Build MLOps pipelines for structured/unstructured data. * Implement observability, monitoring, and ...

YO AI Labs

Senior Software Engineer - Remote

Texas City, TX · Remote

$104K - $138K/yr

Senior Software Engineer Job Type: Contract Location: Remote Job Summary: In this role, you'll ... Deep understanding of algorithms, data structures, and performance tuning. * Demonstrated ...

ICF

Senior Transmission Line Engineer - REMOTE

Houston, TX · Remote

$99K - $137K/yr

Title: Senior Transmission Line Engineer Location: Remote US Ready to make a difference? We are ... Prepare and review technical documentation such as specifications, data sheets, RFQs, bid ...

HungerRush

Menufy GTM Engineer (Remote)

Houston, TX · Remote

As our GTM Engineer, you'll own the infrastructure that connects our data, campaigns, and revenue ... FP&A, Data Science or Statistics to inform decisions. Can take a raw data question and convert it ...

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Financial Data Engineer Remote information

See Houston, TX salary details

$42.5K

$123.9K

$169.5K

How much do financial data engineer remote jobs pay per year?

As of Aug 7, 2026, the average yearly pay for financial data engineer remote in Houston, TX is $123,876.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,300.00 and $131,300.00 per year, depending on experience, location, and employer.

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 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 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.
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Financial Data Engineer Remote jobs near you

Data Engineer

Arva Intelligence

Houston, TX • On-site, Remote

$95K - $130K/yr

Other

Re-posted 20 days ago

Job description

Job Title:                          Data Engineer 

Department:                     Modeling & Analytics

Reports to:                       Lead Modeling Scientist

Location:                          Remote

Base Salary Range:        $95k - $130k

General Position Description

The Data Engineer is responsible for building and scaling the data and computational backbone that supports Arva's ecosystem modeling and measurement, reporting, and verification platforms. This role sits within a multidisciplinary Data Science team and focuses on designing reliable, auditable, and scalable data systems that enable biogeochemical modeling and optimization at production scale.

In this role, the Data Engineer will design and maintain production-grade data pipelines that integrate diverse datasets including field measurements, management practices, soils, and weather with process-based ecosystem models. The role plays a critical part in ensuring data quality, reproducibility, and traceability so that scientific outputs can be translated into trusted, credit-grade results with real-world impact.

Primary Job Responsibilities

Data Pipeline and Workflow Development

  • Design, implement, and maintain scalable data pipelines supporting ecosystem and biogeochemical modeling
  • Build reproducible workflows that generate standardized model inputs and manage outputs across space, time, and scenario analysis
  • Integrate heterogeneous datasets, including field data, management data, soil data, and weather data, into modeling pipelines

Cloud Infrastructure and Data Systems

  • Develop and maintain cloud-based infrastructure to support modeling pipelines and optimization workflows
  • Implement data storage solutions using relational, spatial, and object-based databases
  • Support efficient data access and processing using platforms such as PostgreSQL, PostGIS, and cloud object storage

Data Quality, Governance, and Auditability

  • Ensure data quality, versioning, traceability, and auditability to support measurement, reporting, and verification requirements
  • Implement validation and monitoring processes to ensure reliability of model inputs and outputs
  • Support transparent, repeatable workflows suitable for regulatory and credit market review

Software Engineering and Collaboration

  • Write clean, modular, and well-documented production code that supports maintainable and scalable data systems
  • Apply software engineering best practices including testing, version control, and documentation
  • Collaborate closely with Data Science and Technology teams to align data infrastructure with modeling, analytics, and production needs

Key Competencies / Requirements

  • 3+ years demonstrated experience building and maintaining data pipelines for large, complex, and heterogeneous datasets
  • Strong proficiency in Python and modern data engineering tools, with experience writing production-grade, testable code
  • Experience working with cloud platforms, with AWS strongly preferred
  • Familiarity with containerization tools such as Docker and version control systems such as GitHub
  • Experience with relational and spatial databases, including PostgreSQL and PostGIS
  • Experience working with geospatial data formats and spatial data processing
  • Experience supporting scientific or ecosystem modeling workflows preferred
  • Familiarity with workflow orchestration tools such as Airflow or Prefect preferred
  • Bachelor's or Master's degree or equivalent experience in Data Engineering, Computer Science, Environmental Informatics, or a related field

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