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Remote Oracle Data Engineer Jobs in Houston, TX (NOW HIRING)

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 ...

LiteBridge

Data Engineer (Junior)

Houston, TX · Remote

LiteBridge connects talented data engineers with global opportunities by training them in Palantir ... Flexible, remote work environment. * Placement with international clients upon certification.

Troutman Pepper

Senior Data Engineer

Houston, TX · Remote

$101K - $137K/yr

The Senior Data Engineer is responsible for analyzing, validating, cleansing, and performing ETL of ... Prior law firm or professional services experience beneficial. #LI-Remote The Firm will comply with ...

Atria Group LLC

Oracle WebCenter Sites Admin

Houston, TX · Remote

$21.75 - $27.50/hr

Our company provides application analysis, design, development and programming, software ... Remote Satellite, Community and Gadget Servers) o WebCenter Sites Clustering o Support with Oracle ...

NATIONMIND LLC

Data Analyst

Houston, TX · Remote

$40 - $45/hr

Comfortable working with data engineers to validate datasets, metric logic, and dashboard performance. This is a remote position.

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As of Jul 10, 2026, the average hourly pay for remote oracle data engineer in Houston, TX is $65.58, according to ZipRecruiter salary data. Most workers in this role earn between $58.99 and $73.46 per hour, depending on experience, location, and employer.
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Data Engineer

Arva Intelligence

Houston, TX • On-site, Remote

$95K - $130K/yr

Full-time

Posted 23 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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