Databricks Data Engineer

• Design, develop, and maintain ETL/ELT data pipelines for structured and semi‑structured data
• Build and optimize data lakehouse solutions supporting analytics, reporting, and regulatory needs
• Implement data ingestion from multiple sources (databases, APIs, files, messaging/ event streams)
• Perform data transformation, validation, and quality checks across end‑to‑end data flows
• Collaborate with Business Analysts and stakeholders to translate requirements into data solutions
• Support production environments, handle incident analysis, and contribute to performance optimization
• Ensure compliance with data governance, security, and regulatory standards

Key requirements:

• 5-6 years of experience in Data Engineering with Databricks
• Very strong Python, SQL, and PySpark programming skills
• Experience with Databricks (Delta Lake, DLT) and cloud data lake/lakehouse architectures
• Experience with Azure (ADLS, Data Factory, Synapse) or equivalent cloud services
• Knowledge of Medallion architecture and dimensional models
• Experience with REST APIs, batch and streaming ingestion
• Proficiency in Git, CI/CD pipelines, Azure DevOps or similar
• Strong understanding of data quality, performance tuning, and scalability
• Exposure to banking, risk, regulatory reporting, or analytics platforms
• Experience supporting data-intensive applications used for decision-making and compliance
• Very good English skills

Nice to have:

• Knowledge of Data Vault
• Streaming technologies (Kafka, Event Hub)
• Experience with Power BI or Tableau for data consumption
• Azure or Databricks certifications