Data Engineer

ERM is seeking a Data Engineer to join our Digital Products team. This is an exciting opportunity for an early- to mid-career data professional to support cutting-edge climate science by engineering high-performance data pipelines and workflows in Azure and Microsoft Fabric. The successful candidate will help operationalize global climate model data and other scientific datasets by applying algorithms developed by ERM's climate scientists and consultants, supporting large-scale climate risk assessments across sectors including energy, finance, infrastructure, and natural resources.

You'll work alongside a team of experts in climate science, software development, and environmental consulting. You'll also have access to a global network of technical specialists and opportunities to grow your skills within a purpose-driven organization.

Responsibilities:

• Develop, test, and maintain scalable data pipelines in Azure and Microsoft Fabric to process climate and environmental data.
• Support the application of scientific algorithms to global climate model outputs and other multidimensional datasets (e.g., NetCDF, Zarr).
• Optimize data pipelines for performance, scalability, and reliability, including benchmarking storage read/write speeds and tuning Spark-based workflows.
• Implement logging, monitoring, and metadata management systems for traceability and auditability.
• Evaluate and configure Azure storage (Blob, Data Lake, etc.) for climate-scale workloads; ensure performance alignment with data access needs.
• Build and manage distributed processing pipelines to support large-scale data transformations using PySpark and parallel computing strategies.
• Monitor and optimize I/O performance across workflows and storage tiers.
• Collaborate with climate scientists and software engineers to translate prototype code into scalable, production-ready processes.
• Document data engineering workflows and support internal data governance efforts.

Requirements:

• Bachelor's degree in Computer Science, Data Science, Environmental/Climate Science, Oceanography, or a related field.
• 2+ years of experience in data engineering, including pipeline development and workflow optimization (cloud-based preferred).
• Hands-on experience with Microsoft Azure data services and/or Microsoft Fabric.
• Strong programming skills in Python; experience with Spark (PySpark or SparkSQL) in distributed environments.
• Demonstrated experience working with large, multidimensional datasets (Zarr, NetCDF, HDF5).
• Familiarity with cloud storage performance tuning and benchmarking techniques.
• Experience implementing logging, monitoring, and metadata practices in data environments.
• Strong communication skills, with ability to collaborate across technical and non-technical teams.
• Preferred: Azure Data Engineering certification, or demonstrable equivalent experience.