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Financial Data Engineer Remote Jobs in Houston, TX

Insolation Technology Ltd

Data Analyst

Houston, TX · On-site +1

$21 - $26/hr

Work closely with engineering teams, project managers, and other departments to understand their ... Flexible work schedule and remote work options Job Type: * Full time Pay: * $21.00 - $26.00 per ...

Baker Hughes

Field Service Electrical Engineer

Houston, TX · On-site +1

$60K - $79K/yr

Field Service Electrical Engineer (Remote in Houston) Are you an experienced Field Service Engineer ... Tailored financial programs * Education Assistance * Generous Parental Leave * Mental Health ...

Baker Hughes

Field Service Electrical Engineer

Houston, TX · On-site +1

$60K - $79K/yr

Field Service Electrical Engineer (Remote in Houston) Are you an experienced Field Service Engineer ... Tailored financial programs * Education Assistance * Generous Parental Leave * Mental Health ...

YO AI Labs

AI Consulting Expert - Remote

Houston, TX · Remote

$100 - $200/hr

Annotate data, interpret findings, and perform fact-checking to ensure high-quality content ... Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical & Report Writing

ComboCurve, Inc.

Senior Software Engineer, Python

Houston, TX · On-site +1

$117K - $154K/yr

... data integration and enhancing collaboration, we help operators, engineers, and financial teams ... This is a fully remote position, but candidates will be expected to be in person for initial ...

Deloitte

GCP Engineer

Houston, TX · On-site +1

Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite and/or remote client service delivery. Work you'll do As a GCP Engineer on the AI & Data team, you ...

Initio Capital

Data Governance Analyst

Houston, TX · Remote

... consulting, finance, product, software, AI, operations, market research, and growth-focused ... This is a remote, flexible role for candidates who are analytical, commercially curious, and ...

Initio Capital

Data Integration Analyst

Houston, TX · Remote

... consulting, finance, product, software, AI, operations, market research, and growth-focused ... This is a remote, flexible role for candidates who are analytical, commercially curious, and ...

System One

Accounting Clerk

Houston, TX · Remote

$25/hr

Hybrid - onsite and remote Hours: 40.0 hours per week Security Clearance: Not specified Responsibilities * Support day-to-day financial operations by auditing financial data for accuracy, compliance ...

System One

Accounting Clerk

Houston, TX · Remote

$25/hr

Hybrid - onsite and remote Hours: 40.0 hours per week Security Clearance: Not specified Responsibilities * Support day-to-day financial operations by auditing financial data for accuracy, compliance ...

System One

Accounting Clerk

Houston, TX · Remote

$25/hr

Hybrid - onsite and remote Hours: 40.0 hours per week Security Clearance: Not specified Responsibilities * Support day-to-day financial operations by auditing financial data for accuracy, compliance ...

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Financial Data Engineer Remote information

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$42.5K

$123.9K

$169.5K

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

As of Aug 19, 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 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.

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Financial Data Engineer Remote jobs near you

Data Scientist - Remote

NAVA Software Solutions

Houston, TX • On-site, Remote

Full-time

Re-posted 17 days ago

Job description

NAVA Software solutions is looking for a Data Scientist
Details:
Data Scientist
Location: Houston TX - Remote is ok
Duration: 12 months
Clients want a data scientist who can develop machine learning models to run forecast scenarios. Also, they want this person to be knowledgeable in AWS Cloud technology
A Data Scientist with physical pipeline experience typically specializes in analyzing and optimizing physical infrastructure pipelines, such as those used in the oil and gas industry or transportation networks. Here are some common job duties associated with this role:
  • Data collection and integration: Data scientists with physical pipeline experience gather data from various sources related to the infrastructure pipelines, such as sensors, SCADA (Supervisory Control and Data Acquisition) systems, or IoT devices. They integrate and consolidate the data for analysis and modeling.
  • Pipeline performance analysis: These professionals analyze the performance of physical pipelines by examining data related to flow rates, pressure levels, temperature, corrosion, and other relevant factors. They use statistical techniques and machine learning algorithms to identify patterns, anomalies, and potential issues that may affect pipeline operations.
  • Predictive modeling and maintenance optimization: Data scientists develop predictive models to forecast pipeline performance and detect potential failures or maintenance needs. They utilize historical data, sensor measurements, and other relevant parameters to train models that can predict future events, such as leaks, blockages, or equipment failures. By identifying critical maintenance requirements in advance, they can optimize maintenance schedules and minimize downtime.
  • Risk assessment and mitigation: Data scientists assess risks associated with physical pipelines, such as environmental hazards, security threats, or regulatory compliance. They develop risk assessment models and analyze the impact of different factors on pipeline safety and integrity. Based on these analyses, they propose mitigation strategies to minimize risks and ensure compliance with safety regulations.
  • Optimization of pipeline operations: Data scientists work on optimizing the operational efficiency of physical pipelines. They analyze data to identify areas of improvement, such as reducing energy consumption, optimizing transportation routes, or improving overall system performance. By applying data-driven approaches and algorithms, they provide recommendations to optimize pipeline operations and maximize efficiency.
  • Visualization and reporting: Data scientists with physical pipeline experience create visualizations, reports, and dashboards to communicate their findings and recommendations effectively. They present complex data in a visually understandable format, allowing stakeholders to make informed decisions regarding pipeline maintenance, operations, and risk management.
  • Collaboration with cross-functional teams: These professionals collaborate with engineers, domain experts, operations personnel, and other stakeholders involved in managing physical pipelines. They work together to understand the specific requirements, constraints, and challenges associated with the infrastructure. Effective communication and teamwork are essential to ensure alignment and successful implementation of data-driven solutions.
  • Continuous improvement and innovation: Data scientists keep up with the latest advancements in data science, machine learning, and pipeline technologies. They explore new methodologies, algorithms, and tools to enhance their skills and propose innovative solutions to address pipeline-related challenges.
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About NAVA Software Solutions

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NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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