Senior Data Engineer (Databricks) – Financial Services

Technologies we use

About the project

This is how we organize our work

Team members

Your responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks.
• Build and optimize ETL/ELT processes for large-scale data processing.
• Develop data transformation solutions using PySpark, Python, and SQL.
• Implement and optimize Delta Lake architectures.
• Design and maintain reliable data ingestion and integration processes.
• Improve data quality, performance, and reliability across data platforms.
• Collaborate with Data Architects, Analysts, and business stakeholders to deliver data solutions.
• Ensure data security, governance, and compliance with financial industry standards.
• Troubleshoot and optimize existing data engineering workflows.

Our requirements

• 5+ years of commercial experience in Data Engineering.
• Minimum 3 years of hands-on experience with Databricks.
• Strong practical knowledge of Apache Spark and PySpark.
• Advanced SQL and Python programming skills.
• Experience designing and implementing ETL/ELT pipelines.
• Solid understanding of Delta Lake and Lakehouse architecture.
• Experience working with cloud platforms (Azure, AWS, or GCP).
• Knowledge of data modeling, data warehousing, and data integration.
• Experience optimizing data processing performance and managing large datasets.
• English proficiency at C1 level.

Optional

• Previous experience in banking, insurance, or financial services.
• Experience with Azure Databricks and Azure Data Factory.
• Knowledge of Unity Catalog and Databricks Workflows.
• Experience with CI/CD pipelines and Infrastructure as Code.
• Databricks certifications.
• Understanding of data governance, security, and regulatory requirements in financial environments.