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AI Sustainability Data Engineer

Chloe Schneider

Full-time · Job · Berlin

About the role

ESG reporting used to be a nice-to-have. Now it's mandatory for thousands of European companies, and they don't have the data infrastructure to comply. Our platform automates ESG data collection, validation, and reporting — pulling from utility bills, supply chain records, travel logs, and HR systems to calculate carbon footprints and social impact metrics. You'll build the data pipelines that make this possible: ingesting messy data from 50+ source types, normalizing units and formats, calculating emissions factors, and delivering clean datasets to our reporting engine. The pipeline runs on Airflow with Snowflake as the analytical layer. Sustainability data is uniquely messy — every client measures things differently, units are inconsistent, and data gaps are common. You'll need creative approaches to data quality that go beyond standard validation checks.

Responsibilities

  • Build ETL pipelines ingesting ESG data from 50+ source types
  • Normalize and validate sustainability metrics across inconsistent formats
  • Calculate emissions factors and carbon footprint metrics
  • Design data quality frameworks for handling gaps in sustainability data
  • Maintain Airflow DAGs and Snowflake schemas for ESG reporting

Requirements

  • 3+ years in data engineering with Python and SQL
  • Experience with Airflow for pipeline orchestration
  • Familiarity with Snowflake or similar cloud data warehouses
  • Comfort with messy, inconsistent data sources
  • Interest in sustainability, ESG reporting, or climate data

Benefits

  • Fully remote — European time zones
  • 30 days PTO
  • Home office budget
  • Impact on corporate sustainability and climate reporting

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

data science & analytics MLOps & AI Infrastructure

Skills

python sql airflow snowflake pandas docker aws

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