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Remote Data Processing Jobs in Houston, TX (NOW HIRING)

Data Engineer

Houston, TX ยท On-site +1

$95K - $130K/yr

Remote Base Salary Range: $95k - $130k General Position Description The Data Engineer is ... Support efficient data access and processing using platforms such as PostgreSQL, PostGIS, and cloud ...

Data Engineer

Houston, TX ยท On-site +1

$95K - $130K/yr

Remote Base Salary Range: $95k - $130k General Position Description The Data Engineer is ... Support efficient data access and processing using platforms such as PostgreSQL, PostGIS, and cloud ...

Drive harmonization of relevant Master Data processes across in Wesco to provide a common and ... Ability to travel up to 25% #LI-JB1 #LI-REMOTE This amount is what we reasonably believe we will ...

Data Analyst

Houston, TX ยท On-site +1

$21 - $26/hr

The Data Analyst will be responsible for collecting, processing, and analyzing data to support ... Flexible work schedule and remote work options Job Type: * Full time Pay: * $21.00 - $26.00 per ...

Data Analyst

Houston, TX ยท Remote

$40 - $45/hr

Houston, TX or US Remote Duration: 6-12 months Skills: Data Analytics & Insights : ignio AIOps Experience Required: 6-8 Years Role Description: Data Analyst Strong experience in data analysis ...

Remote 100% within Texas only Why Us. UT MD Anderson offers the opportunity to lead transformative ... governance processes through ingestion, ingress, egress, curation, pipeline development ...

Senior Software Engineer, Python

Houston, TX ยท On-site +1

$117K - $154K/yr

This is a fully remote position, but candidates will be expected to be in person for initial ... Create high-performance data processing paths inside services to support analytics and ingestion ...

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Remote Data Processing information

See Houston, TX salary details

$11

$19

$33

How much do remote data processing jobs pay per hour?

As of Aug 3, 2026, the average hourly pay for remote data processing in Houston, TX is $19.35, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $21.35 per hour, depending on experience, location, and employer.

What is the difference between Remote Data Processing vs Remote Data Analysis?

AspectRemote Data ProcessingRemote Data Analysis
Primary RoleHandling data input, cleaning, and preparationInterpreting data to generate insights and reports
Skills & CertificationsData management, SQL, basic scriptingStatistical analysis, data visualization, tools like Excel, R, Python
Work EnvironmentData warehouses, cloud platforms, databasesAnalysis tools, dashboards, reporting software
Industry UsageData management teams, IT departmentsBusiness intelligence, marketing, finance

Remote Data Processing focuses on preparing and managing raw data, while Remote Data Analysis involves interpreting that data to inform decisions. Both roles often require similar technical skills but differ in their core responsibilities and end goals.

What are some common challenges faced by professionals in remote data processing roles, and how can they be overcome?

Remote data processing professionals often encounter challenges such as ensuring data accuracy, managing large datasets, and maintaining clear communication with distributed teams. To overcome these, it's important to establish strong data validation protocols, use reliable tools for data management, and schedule regular virtual meetings to stay aligned with team objectives. Additionally, setting clear expectations and using collaborative platforms can help mitigate misunderstandings and improve workflow efficiency.

What is remote data processing?

Remote data processing refers to the collection, analysis, and management of data from a location outside of a traditional office setting, often using cloud-based tools and remote access technologies. Professionals in this role handle data entry, validation, organization, and sometimes basic analytics, ensuring data integrity and accessibility for organizations. This job typically requires strong computer skills, attention to detail, and the ability to work independently while maintaining data security and privacy protocols.

What are the key skills and qualifications needed to thrive as a remote data processing specialist?

To thrive as a Remote Data Processing specialist, you need strong analytical skills, attention to detail, and proficiency in data entry and management, often supported by a relevant degree or experience in data-related roles. Familiarity with databases, spreadsheet software like Microsoft Excel or Google Sheets, and sometimes data processing tools such as SQL or Python is typically required. Excellent time management, self-motivation, and clear communication are essential soft skills for remote collaboration and meeting deadlines. These abilities ensure data accuracy, efficient processing, and effective teamwork in a remote work environment.
What are the most commonly searched types of Data Processing jobs in Houston, TX? The most popular types of Data Processing jobs in Houston, TX are:
What cities near Houston, TX are hiring for Remote Data Processing jobs? Cities near Houston, TX with the most Remote Data Processing job openings:
Infographic showing various Remote Data Processing job openings in Houston, TX as of July 2026, with employment types broken down into 81% Full Time, 5% Part Time, 3% Temporary, and 11% Contract. Highlights an 100% Remote job distribution, with an average salary of $40,255 per year, or $19.4 per hour.

Data Engineer

Arva Intelligence

Houston, TX โ€ข On-site, Remote

$95K - $130K/yr

Full-time

Re-posted 17 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 Arvaโ€™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
  • Bachelorโ€™s or Masterโ€™s degree or equivalent experience in Data Engineering, Computer Science, Environmental Informatics, or a related field