Senior Data Engineer – Azure Lakehouse & Data Products

Capitole Consulting; Bellprat; On-site; EUR 75,000 - 110,000; Full time

Benefits offered by this job

Professional development

Monthly feedback

Health insurance

Meal vouchers

Transport vouchers

Childcare vouchers

Wellhub access

Capitole Club discounts

Job summary

Capitole Consulting is seeking a Senior Data Engineer to help evolve our Azure-based Data Platform and Lakehouse architecture. You will drive data product development, building pipelines in ADF and Airflow and working with Databricks to transform business needs into reliable data products.

You will lead data pipeline implementations, optimize performance and collaborate with POs to refine requirements, ensuring robust, observable data solutions across the data stack.

Qualifications

• 6+ years of experience in data engineering.
• Strong PySpark and SQL skills.
• Hands-on with Azure-based data platforms (Databricks, Unity Catalog).
• Experience with Airflow and Data Factory for orchestration.
• Knowledge of Data Warehouse, Lakehouse architectures and Medallion layers.

Responsibilities

• Build scalable, reliable data pipelines using Azure Data Factory and Airflow.
• Develop transformations in Azure Databricks (PySpark/SQL) for data products.
• Refine requirements with Product Owners and translate into Data Products.
• Optimize performance, cost, and reliability of data workloads.
• Participate in architecture reviews and code/design reviews.
• Assist Run/Operations with production pipelines and incident resolution.

Skills

Data engineering

Python

PySpark

SQL

Azure

Databricks

Airflow

ADF

Tools

Azure Databricks

Unity Catalog

Apache Airflow

Azure Data Factory

Power BI

Tableau

Job description

Capitole Consulting is seeking a Senior Data Engineer to help evolve our Azure-based Data Platform and Lakehouse architecture. You will drive data product development, building pipelines in ADF and Airflow and working with Databricks to transform business needs into reliable data products.

You will lead data pipeline implementations, optimize performance and collaborate with POs to refine requirements, ensuring robust, observable data solutions across the data stack.