Senior Data Engineer: Azure Data Pipelines & Analytics

PUR; Paris; Sur place; EUR 80 000 - 110 000; Plein temps

Résumé du poste

PUR is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines powering analytics and reporting. You will transform raw project data into clean, high-quality datasets through robust ETL processes and modern architectures, partnering with business and technical stakeholders.

You will contribute to a cloud-first data platform, emphasize data reliability, and implement best practices across the data ecosystem while collaborating with cross-functional teams to deliver

Qualifications

• 3–5 years of experience in Data Engineering.
• Strong Python skills and production-grade ETL experience.
• Strong SQL, relational databases, data warehousing concepts.
• Experience with workflow orchestration tools and automated testing for data pipelines.
• Cloud experience with Azure and IaC tooling.

Responsabilités

• 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.

Connaissances

Python

SQL

ETL pipelines

Data modeling

Airflow/Prefect/Dagster

Azure

Terraform

Git

Data quality

English communication

Outils

Airflow

Prefect

Dagster

Terraform

Azure

Description du poste

PUR is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines powering analytics and reporting. You will transform raw project data into clean, high-quality datasets through robust ETL processes and modern architectures, partnering with business and technical stakeholders.

You will contribute to a cloud-first data platform, emphasize data reliability, and implement best practices across the data ecosystem while collaborating with cross-functional teams to deliver