• Data Engineer II

    Insight Global (Seattle, WA)


    Job Description

    Are you passionate about using data and AI to drive environmental innovation at global scale? A large technology company in the Seattle area is looking to add a Machine Learning Data Engineer to join their team. 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.

     

    We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

    Skills and Requirements

    • 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. · 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.