Senior Data Engineer
At a glance
Senior Data Engineering role at PUR. Paris · full-time · no salary stated · we estimate €60,000–€62,500 across France.
PUR has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Build and maintain Python pipelines that move and transform project data for analytics and reporting
- Shape large datasets through ingestion, transformation and validation, then maintain models for reporting and business applications
- Set up data quality checks and monitor reliability and accuracy
- Run workflows with Airflow, Prefect or Dagster, and help improve cloud data platforms, preferably Azure
- Support testing, CI/CD, monitoring and infrastructure-as-code work, while documenting engineering practices
What you bring
- Three to five years in data engineering, including strong Python skills and production ETL pipeline experience
- Strong SQL skills and knowledge of relational and analytical databases, data modeling and warehousing
- Experience with workflow orchestration and automated testing for data pipelines
- Hands-on cloud platform experience and strong Git and software engineering practices
- Fluent English, with clear written and spoken communication
Who this fits
This role suits a senior data engineer who works across technical and business teams and prioritizes dependable, high-quality data. The position is full-time and based in Paris, with hybrid work.
From the employer
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.
We are looking for someone with:
3-5 years of experience in Data Engineering, with strong Python skills and experience building production-grade ETL pipelines.
Strong SQL expertise and solid understanding of relational and analytical databases, data modeling, and data warehousing concepts.
Experience with workflow orchestration tools (Airflow, Prefect, Dagster) and implementing automated testing for data pipelines.
Hands-on experience with cloud platforms (preferably Azure) and Infrastructure as Code tools (Terraform is a strong plus).
Familiarity with AI tools (Claude is a plus).
Strong knowledge of Git and software engineering best practices.
Excellent problem-solving skills, focus on data quality and reliability, and ability to collaborate with cross-functional stakeholders.
Fluent English with strong written and verbal communication skills.
Recruitment process :
Interview with the recruiter
Interview with the manager and case study
References check
At PUR, we strive to build inclusive teams and an equitable workplace where our employees feel respected, supported, and empowered. As a global company operating across six continents, we recognize that diversity in the workplace is essential to achieving our mission.
We welcome applications from all qualified candidates regardless of age, race, gender, colour, religion, national origin, sexual orientation, gender identity, disability, or any other aspect that makes them unique.
PUR is dedicated to providing an accessible environment for all candidates during the application process and for employees during their employment. If you require accommodation or consideration throughout the interview process, let us know, and we will do our best to support you.
Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Data Engineering
Find me workBy the team behind dataroles.