Senior Data Developer (Azure and Databricks)

Responsibilities:

• Develop and maintain data pipelines using Databricks, PySpark, Python, and SQL to transform raw financial data into reliable, curated datasets.
• Integrate new data sources, support financial reconciliation, P&L routines, and global closing processes, ensuring data consistency and accuracy.
• Collaborate with multidisciplinary teams to deliver high-quality data solutions, support AI initiatives, and implement continuous improvements in data performance and quality.

Requirements:

• Solid experience with Databricks, including notebooks, jobs, workflows, cluster management, and best practices for scalable data solutions.
• Strong proficiency in PySpark, Python, and SQL for transforming raw data into curated, reliable datasets.
• Experience with Azure data ecosystem, specifically Azure Data Lake Storage, cloud integration patterns, and cloud data processing.

Differentiators:

• Familiarity with AI frameworks and methodologies applied to data workflows.
• Experience with advanced Databricks features such as Workflows, Apps, or Streamlit-based applications.
• Previous experience in financial services or payments, including acquiring, transaction processing, or fintech environments.