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Remote Data Infrastructure 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 ... Develop and maintain cloud-based infrastructure to support modeling pipelines and optimization ...

NRG Energy

Sr Data Scientist

Houston, TX · On-site +1

Houston, TX 4 days onsite. Fridays are remote. Department: Customer Success, Continuous Improvement ... Data Engineering & MLOps Infrastructure: Partner with data teams using Databricks, Spark, SQL, and ...

Huntington

Enterprise Architect (IT)

Houston, TX · On-site +1

$66 - $85/hr

Facilitate alignment across application, data, integration, infrastructure, cloud, and security ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Huntington

Enterprise Architect (IT)

Houston, TX · On-site +1

$102K - $208K/yr

Facilitate alignment across application, data, integration, infrastructure, cloud, and security ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

GAI Consultants

Data Center Program Manager

Houston, TX · On-site +1

$112K/yr

Enjoy flexible work arrangements (remote/hybrid options available). * Access a comprehensive ... infrastructure, we don't just support--we innovate. Our collaborative approach ensures every ...

Huntington

Application Architect (IT)

Houston, TX · On-site +1

$70K - $140K/yr

Experience across business, application, data, infrastructure, security, cloud, and integration ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Huntington

Application Architect (IT)

Houston, TX · On-site +1

Experience across business, application, data, infrastructure, security, cloud, and integration ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

NAVA Software Solutions

AI Engineer -Remote

Houston, TX · On-site +1

Guide architecture, infrastructure, and tools for AI/ML products. * Develop rapid prototypes and ... Build MLOps pipelines for structured/unstructured data. * Implement observability, monitoring, and ...

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Remote Data Infrastructure information

What are the key skills and qualifications needed to thrive as a Remote Data Infrastructure Engineer, and why are they important?

To excel as a Remote Data Infrastructure Engineer, you need a strong background in computer science, data architecture, and experience with cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with tools like Terraform, Kubernetes, and data pipeline technologies, as well as relevant certifications (e.g., AWS Certified Solutions Architect), is typically required. Strong problem-solving abilities, clear communication, and self-motivation are essential soft skills for remote collaboration and troubleshooting. These competencies ensure reliable, scalable data systems and effective teamwork across distributed environments.

What are some common challenges faced by professionals working in remote data infrastructure roles?

Professionals in remote data infrastructure roles often encounter challenges such as ensuring seamless communication across distributed teams, maintaining high availability and performance of data systems, and managing security risks associated with remote access. Coordinating with colleagues across different time zones can require flexibility in scheduling and proactive communication. Additionally, remote data infrastructure engineers must stay up-to-date with evolving cloud technologies and best practices to effectively support scalable, reliable, and secure data architectures.

What is remote data infrastructure?

Remote data infrastructure refers to the systems, tools, and processes that enable organizations to collect, store, manage, and analyze data from remote locations, often via cloud-based platforms. This infrastructure allows teams to access and work with data securely from anywhere, supporting distributed work environments and scalable data solutions. It typically involves cloud storage, data pipelines, databases, and security protocols tailored for remote accessibility. Remote data infrastructure is essential for businesses that operate in multiple locations or have remote teams.
What are the most commonly searched types of Data Infrastructure jobs in Houston, TX? The most popular types of Data Infrastructure jobs in Houston, TX are:
What are popular job titles related to Remote Data Infrastructure jobs in Houston, TX? For Remote Data Infrastructure jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Remote Data Infrastructure jobs in Houston, TX look for? The top searched job categories for Remote Data Infrastructure jobs in Houston, TX are:
What cities near Houston, TX are hiring for Remote Data Infrastructure jobs? Cities near Houston, TX with the most Remote Data Infrastructure job openings:
Remote Data Infrastructure jobs near you
Infographic showing various Remote Data Infrastructure job openings in Houston, TX as of July 2026, with employment types broken down into 69% Full Time, 6% Part Time, and 25% Contract. Highlights an 100% Remote job distribution.

Data Engineer

Arva Intelligence

Houston, TX • On-site, Remote

$95K - $130K/yr

Other

Posted 9 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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