Senior Data Engineer

Job title: Senior Data Engineer

Department: Data team

Reports to: Lead Data Engineer

Location: Paris, France

Contract: Permanent, local and full-time 

Starting date: ASAP 2026

PUR Description 

PUR is a global B Corp helping companies act for climate, nature and people through nature-based projects. 

Since 2008, we have worked with leading companies to restore ecosystems, support farmers and communities, and build more resilient supply chains. Our projects include agroforestry, regenerative agriculture, reforestation, and ecosystem restoration, across more than 30 countries. 

We work closely with local partners, farmers, cooperatives, NGOs and businesses to design projects that are adapted to each landscape and community. This local approach is key to creating long-term impact — for the climate, biodiversity, soil, water, and livelihoods. 

Today, PUR has more than 200 team members across 16 countries, with key offices in Paris and Toronto. As the world faces growing climate and biodiversity challenges, PUR is helping global companies move from ambition to action. 

About the role 

As a Senior Data Engineer, you will design, develop, and maintain scalable data pipelines and data processing solutions that power analytics, reporting, and data-driven decision making. You will play a key role in transforming raw project data into reliable, high-quality datasets through robust ETL processes, modern data architectures, and Python-based engineering practices. 

Working closely with business and technical stakeholders, you will ensure that data is accessible, trustworthy, and aligned with analytical requirements while contributing to the continuous improvement of our data platform and cloud-based ecosystem. 

Your responsibilities will be, but not limited to: 

• Design, develop, and maintain scalable ETL/ELT pipelines using Python.

• Build and optimize data ingestion, transformation, and validation processes for large datasets.

• Design and maintain data models supporting reporting, analytics, and business applications.

• Implement and monitor data quality controls to ensure reliability and accuracy.

• Manage and optimize workflows using orchestration tools such as Airflow, Prefect, or Dagster.

• Contribute to the development and maintenance of cloud-based data platforms (preferably Azure).

• Support CI/CD, testing, monitoring, and infrastructure-as-code practices (Terraform).

• Collaborate with cross-functional teams to deliver scalable and reliable data solutions.

• Maintain technical documentation and promote data engineering best practices.