Senior Data Engineer

Carbonfuture is the Trust Infrastructure for durable carbon removal. Today, the Trust Infrastructure consists of two products that seamlessly connect the entire carbon removal lifecycle: Carbonfuture MRV+, the most comprehensive MRV solution for durable CDR, and Carbonfuture Marketplace, the leading marketplace for durable CDR. At Carbonfuture, we build trust throughout the carbon removal journey with our rigorous, data-driven approach, ensuring unmatched quality and reliability of carbon removal. We empower suppliers by providing the essential project support and finance needed to transform their carbon removal projects into fully certified carbon credits. For corporate buyers, we offer access to portfolios of carbon removal credits adhering to the highest quality standards and provide visibility at each step of the carbon removal lifecycle via data-driven transparency enabled by Carbonfuture MRV+. We work with some of the world's most ambitious climate leaders such as Microsoft, Swiss Re, and the World Economic Forum First Movers Coalition.

Your role & responsibility

As a Senior Data Engineer at Carbonfuture, you will lead the design and implementation of scalable, high-impact data solutions that drive our mission to scale durable carbon removal. You’ll take ownership of critical parts of our data infrastructure, shape the future of our analytics strategy, and mentor others while collaborating closely with cross-functional teams. Your work will directly support data-driven decision-making for internal stakeholders, suppliers, and partners across the carbon removal ecosystem.

What you’ll do:

• Design and build robust, scalable data pipelines (ETL/ELT) using Python, SQL, dbt, and Spark/Snowpark.
• Own and evolve our data architecture across platforms like BigQuery, Azure Data Lake, or S3, ensuring high performance and flexibility.
• Implement data quality monitoring, validation, and enforce clear data contracts.
• Develop and maintain modular analytics layers and ML-ready datasets using modern formats (e.g., Parquet, Iceberg).
• Enable self-service analytics through well-modeled data and intuitive Power BI dashboards.
• Collaborate with cross-functional teams to translate business needs into data solutions.
• Drive engineering excellence through mentorship, documentation, and best practices.

What you’ll bring to the table:

• Strong skills in SQL and Python, with experience across data warehouses.
• Experience with at least one of the following: Apache Spark, PySpark, dbt, Snowpark, Hive, or Hadoop MapReduce.
• Experience with at least one of the following data storage systems: HDFS, Azure Data Lake (ADLS), Amazon S3/EMR, or Google BigQuery/GCS.
• Familiarity with common data formats (e.g., Parquet, ORC, Avro, Iceberg).
• Experience building ETL/ELT pipelines and working with Power BI or other BI tools.
• A strategic mindset with the ability to design scalable data solutions.
• A self-starter with a passion for using data to combat the climate crisis.
• 5+ years of experience in data engineering or analytics, or equivalent academic background.
• Degree in a relevant field (e.g., Computer Science, Engineering, Statistics) is a plus.
• Excellent communication skills in English.

Candidates from cultures and backgrounds underrepresented in VC-backed startups and the climate space are strongly encouraged to apply. A diverse and inclusive workplace where we learn from each other is an integral part of our culture. We actively welcome people of different backgrounds, experiences, abilities, and perspectives. We are an equal-opportunity employer. In the case of equal suitability, preference is given to structurally discriminated individuals.

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Which trade-offs have you faced when designing data models to serve both analytics and operational needs? How did you resolve them? (Please keep it short) *

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Carbonfuture GmbH