Senior Data Engineer

LE PUR
Paris, France
26 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours
Languages
English
Job source

Tech stack

Artificial Intelligence Airflow Automation of Tests Microsoft Azure Big Data Business Software Databases Continuous Integration Information Engineering Data Infrastructure Extract Transform Load (ETL) Data Systems
+13 more
Data Warehousing Decision Support Systems Python (Programming Language) DataOps Software Construction Workflow Management Systems Data Processing Cloud Platform System Data Ingestion Git Infrastructure Automation Frameworks Terraform Data Pipelines

Job description

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., * 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.

Requirements

  • 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.

About the company

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.

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Good distractions

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