Data Engineer

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 Arvas 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
• Bachelors or Masters degree or equivalent experience in Data Engineering Computer Science Environmental Informatics or a related field