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Remote Data Engineer Jobs in Spring, 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 ...

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.

Gainwell Technologies LLC

Business Data Engineer

Houston, TX · On-site +1

$72K - $104K/yr

Summary As a Business Data Engineer at Gainwell, you can contribute your skills as we harness the ... Fully Remote Opportunity within the US * Required Travel 0-10% * Video cameras must be used during ...

ComboCurve, Inc.

Senior Data Engineer, Python

Houston, TX · On-site +1

$109K - $131K/yr

By streamlining data integration and enhancing collaboration, we help operators, engineers, and financial teams make informed decisions faster. Trusted by top energy companies, ComboCurve delivers ...

Deloitte

AI and Data Science Engineer III

Houston, TX · On-site +1

$109K - $131K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We ...

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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All JobsRemote Data Engineer JobsRemote Data Engineer Jobs in Spring, TX

Remote Data Engineer information

See Spring, TX salary details

$39.6K

$115.4K

$158K

How much do remote data engineer jobs pay per year?

As of Jun 22, 2026, the average yearly pay for remote data engineer in Spring, TX is $115,433.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,900.00 and $122,400.00 per year, depending on experience, location, and employer.

What Does a Remote Data Engineer Do?

As a remote data engineer, you focus on collecting, storing, and organizing large amounts of information. You work from home to design, develop, and maintain systems for the mining, warehousing, and processing of data. A data engineer communicates with employers, clients, or other data professionals to assess the needs of the project and develop and implement solutions to meet those needs. Data engineers also take steps to manage current database architecture and make updates when needed. Remote engineers typically handle their responsibilities in a cloud-based environment using “big data” tools, such as Amazon Web Services (AWS) and SQL.

Can a data engineer work remotely?

Yes, data engineers can work remotely, especially as many companies adopt flexible work arrangements. Remote data engineering roles often require strong skills in cloud platforms, data pipelines, and collaboration tools, and may involve regular virtual communication with teams. The feasibility depends on the company's policies and the specific job requirements.

Will AI replace data engineer?

AI is unlikely to fully replace data engineers, as their role involves designing, building, and maintaining data pipelines and infrastructure that require human oversight and expertise. Instead, AI tools can augment their work by automating routine tasks, allowing data engineers to focus on complex problem-solving and system architecture. Skills in programming, cloud platforms, and data management remain essential for the role.

What is the difference between Remote Data Engineer vs Remote Data Analyst?

AspectRemote Data EngineerRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related; SQL, Python, cloud certificationsBachelor's in Statistics, Data Science, or related; SQL, Excel, visualization tools
Work EnvironmentCollaborates with data engineering teams, cloud platforms, big data toolsWorks with business teams, dashboards, reporting tools
Industry UsageTech, finance, healthcare, e-commerceMarketing, finance, retail, healthcare
Common Search IntentBuilding data pipelines, data infrastructureData reporting, insights, visualization

Remote Data Engineers focus on designing and maintaining data pipelines and infrastructure, often requiring programming and cloud skills. Remote Data Analysts interpret data, create reports, and provide insights using visualization tools. While both roles work with data, their responsibilities and skill sets differ, making each suited for different career paths within data teams.

How do remote Data Engineers typically collaborate with other team members across different time zones?

Remote Data Engineers often work with cross-functional teams, including data scientists, analysts, and software engineers, many of whom may be located in different parts of the world. Collaboration is usually facilitated through project management tools, version control platforms, and regular virtual meetings. It’s common to have a mix of synchronous check-ins and asynchronous communication, allowing for flexible scheduling and efficient handoffs. Strong written communication skills and proactive status updates are essential for staying aligned with team objectives and project deadlines.

What is a Remote Data Engineer?

A Remote Data Engineer is a professional who designs, builds, and maintains data pipelines, databases, and data processing systems while working from a location outside of a traditional office. They collaborate with data scientists, analysts, and other stakeholders to ensure data is collected, stored, and made accessible efficiently and securely. Remote Data Engineers use programming languages like Python or Scala, work with technologies such as SQL, Hadoop, or cloud platforms, and address challenges related to data quality and scalability. Their remote role allows them to work for companies regardless of geographic location, often relying on virtual collaboration tools to stay connected with their teams.

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

To thrive as a Remote Data Engineer, you need strong programming skills in languages like Python or Scala, expertise in SQL, data modeling, and a background in computer science or a related field. Familiarity with cloud platforms (such as AWS, Azure, or GCP), big data tools (like Hadoop and Spark), and certifications in cloud or data engineering are highly valued. Excellent problem-solving, communication, and self-management skills help remote data engineers collaborate effectively and stay productive in a distributed environment. These competencies ensure reliable data pipelines, scalable solutions, and seamless teamwork, which are critical for organizational success in data-driven projects.

What engineers make $500,000?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires specialized certifications, leadership roles, and a strong track record of managing complex data infrastructure.

How to make $1000 a week remote?

A remote data engineer can earn $1000 or more per week by working full-time for a company, freelancing on project-based platforms, or offering specialized skills such as data pipeline development, cloud computing, or machine learning. Building a strong portfolio, gaining relevant certifications, and mastering tools like SQL, Python, and cloud services can increase earning potential.
More about Remote Data Engineer jobs
What are the most commonly searched types of Data Engineer jobs in Spring, TX? The most popular types of Data Engineer jobs in Spring, TX are:
What are popular job titles related to Remote Data Engineer jobs in Spring, TX? For Remote Data Engineer jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Remote Data Engineer jobs in Spring, TX look for? The top searched job categories for Remote Data Engineer jobs in Spring, TX are:
What cities near Spring, TX are hiring for Remote Data Engineer jobs? Cities near Spring, TX with the most Remote Data Engineer job openings:
Remote Data Engineer jobs near you
Infographic showing various Remote Data Engineer job openings in Spring, TX as of June 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 100% Remote job distribution, with an average salary of $115,433 per year, or $55.5 per hour.

Data Engineer

Arva Intelligence

Houston, TX • On-site, Remote

$95K - $130K/yr

Full-time

Posted 5 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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