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Data Engineer C2C Remote 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.

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.

Airswift

Software Engineer I

Houston, TX · On-site +1

W2 Contract (C2C is not available) Duration: 12 months (possibility for extension) Location ... The position has evolved from a data science focus into a software engineering-first role ...

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All JobsData Engineer C2C Remote JobsData Engineer C2C Remote Jobs in Spring, TX

Data Engineer C2C Remote information

See Spring, TX salary details

$39.6K

$115.4K

$158K

How much do data engineer c2c remote jobs pay per year?

As of Jun 23, 2026, the average yearly pay for data engineer c2c remote 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 are some common challenges Data Engineers face when working in a fully remote, C2C (Corp-to-Corp) arrangement?

Data Engineers working remotely on a C2C basis often encounter challenges such as aligning with distributed teams across different time zones, ensuring secure data access, and managing communication with multiple stakeholders. Since C2C roles are typically contract-based, there can be less direct oversight and more emphasis on delivering results independently, which requires strong self-management and proactive reporting. Additionally, integrating with existing data infrastructure remotely may involve navigating different security protocols and adapting to each client’s unique tech stack.

What are the key skills and qualifications needed to thrive as a Data Engineer in a remote C2C (Corp-to-Corp) setting, and why are they important?

To thrive as a Data Engineer C2C Remote, you need expertise in data modeling, ETL processes, and proficiency in programming languages like Python or SQL, typically supported by a degree in computer science or a related field. Familiarity with cloud platforms (e.g., AWS, Azure), big data tools (like Hadoop or Spark), and relevant certifications (such as AWS Certified Data Analytics) is highly valued. Strong problem-solving, communication, and self-motivation skills help you collaborate effectively and manage projects independently in a remote environment. These skills and qualities are crucial for building scalable data solutions, ensuring data integrity, and delivering results in a distributed team setting.

What are Data Engineer C2C Remote jobs?

Data Engineer C2C Remote jobs refer to contract positions for data engineers that are fulfilled remotely and use a 'Corp-to-Corp' (C2C) arrangement. In C2C, a contractor works through their own corporation or as part of a consulting company rather than as a direct employee or individual contractor (W2 or 1099). Data engineers in these roles are responsible for designing, building, and maintaining data pipelines and infrastructure, usually for clients across different locations. These remote roles offer flexibility in work location and are common in the tech industry, especially for specialized projects.
What are popular job titles related to Data Engineer C2C Remote jobs in Spring, TX? For Data Engineer C2C Remote jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Data Engineer C2C Remote jobs in Spring, TX look for? The top searched job categories for Data Engineer C2C Remote jobs in Spring, TX are:
What cities near Spring, TX are hiring for Data Engineer C2C Remote jobs? Cities near Spring, TX with the most Data Engineer C2C Remote job openings:
Data Engineer C2C Remote jobs near you
Infographic showing various Data Engineer C2C Remote job openings in Spring, TX as of June 2026, with employment types broken down into 4% As Needed, 83% Full Time, 9% Part Time, and 4% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% 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 6 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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