Data Engineer II (USC Only)

• Are you passionate about using data and AI to drive environmental innovation at global scale.
• We’re looking for a Machine Learning Data Engineer to join clients AI for Sustainability team, part of the Worldwide Sustainability Science & Innovation (SSI).
• In this role, you’ll build and optimize the data pipelines that power next-generation AI models tackling some of the world’s most pressing sustainability challenges in human rights and environmental due diligence across our supplier base.
• Story Behind the Need – Business Group & Key Projects

Reason for Request:

Team culture:

• You’ll collaborate closely with Applied Scientists, Machine Learning Engineers, and domain experts to design end-to-end data systems that turn raw, complex datasets into AI ready workloads.
• This is a highly visible, hands-on opportunity to shape how client applies AI to advance sustainability at scale.

Typical Day in the Role: 

Daily responsibilities:

• Design and maintain scalable, automated data pipelines for diverse data types (text, imagery, logs, geospatial, sensor data, and more).
• Transform, clean, and enrich data for machine learning and AI model training.
• Collaborate with cross-functional teams to understand data requirements and align them with business and scientific goals.
• Improve data quality, observability, and lineage tracking across sustainability data assets.
• Optimize performance and scalability using AWS-native technologies such as S3, Glue, Lambda, Redshift, and Athena.
• Support ML workflows by enabling reproducible data ingestion, transformation, and feature engineering.

• 3+ years of professional experience as a Data Engineer or Machine Learning Data Engineer.
• Familiarity/High-level understanding of common ML/AI techniques.
• Proficiency in Python and SQL for data manipulation and automation.
• Experience with data pipeline frameworks (e.g., Apache Airflow, Spark, or AWS Glue), PySpark, Pandas, and data modeling for ML workflows.
• Knowledge of data quality, observability, and governance frameworks.
• Strong working knowledge of AWS services or other cloud services providers for data processing and analytics.
• Preferred Qualifications · Experience preparing datasets for machine learning or AI models (e.g., feature stores, labeling, or training data curation).
• Familiarity with geospatial, environmental, or sustainability datasets. · Demonstrated passion for AI, sustainability, or environmental impact work.

Additional Information

• Contract Duration: 8 months (extendable to convert to blue badge depending on performance)
• Location: Onsite in Seattle, WA (5 days per week) - highly preferred.
• Remote option possible if candidate is an exceptional fit.

Top 3 must-have hard skills 

• High-level understanding of common ML/AI techniques.
• Proficiency in Python and SQL for data manipulation and automation.
• Experience with data pipeline frameworks (e.g., Apache Airflow, Spark, or AWS Glue), PySpark, Pandas, and data modeling for ML workflows.
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