Senior Data Engineer (Azure Databricks)

About the role

Applaudo, an AI-native organization building AI-powered solutions, is looking for a Senior Data Engineer focused on building scalable, production-grade data pipelines. The role uses Azure Databricks, Python and Spark to connect data across business platforms and feed a centralized Data Hub, with collaboration with a US-based team.

Key responsibilities

• Design, build and maintain production-grade data pipelines using Azure Databricks and Python.
• Develop scalable transformations with PySpark or Spark SQL to integrate data from multiple business systems.
• Ingest and process data from APIs, relational databases, cloud storage and SFTP sources.
• Integrate data from ticketing, CRM, marketing, retail and other enterprise platforms into a Data Hub.
• Build and maintain data warehouse structures, dimensional models and data marts.
• Write, optimize and maintain SQL transformations; implement data quality checks and consistency validations.
• Maintain outbound data feeds for third-party systems and document pipelines and their dependencies.
• Troubleshoot pipeline failures and data discrepancies, and communicate progress and blockers proactively.

Required profile

• 5+ years of professional experience in data engineering, designing and maintaining production pipelines.
• Hands-on experience with Azure Databricks, advanced Python, Apache Spark (PySpark and/or Spark SQL) and advanced SQL.
• Knowledge of data warehousing and dimensional modeling, and experience integrating data from multiple sources.
• Ability to work autonomously, follow documentation standards and communicate clearly in English with a US-based team.
• Nice to have: experience migrating SQL-based workloads to Azure Databricks.