Job Requirements 

• Bachelor’s degree in Computer Science, Information Technology, or a related field;
• More than 4 years of experience in data engineering, big data, or cloud-based analytics, with a strong preference for experience in banking or fintech sector;
• More than 2 years of hands-on experience with Databricks (Workflows, Jobs, Notebooks, and Clusters), including Delta Lake, Spark Structured Streaming;
• Expertise in Apache Spark (PySpark/Scala) for large-scale data processing and real-time analytics;
• Advanced experience in SQL and Python/Scala, with experience in data transformations and ETL pipelines;
• Strong understanding of Delta Lake architecture for data versioning, ACID transactions, and schema evolution;
• Experience with Cloud Platforms, particularly Databricks on Azure;
• Knowledge of Lakehouse architecture and designing scalable, secure, and cost-efficient data pipelines (is a plus);
• Familiarity with streaming architectures (Kafka) is a plus;
• Experience in MLOps and model deployment using MLflow in Databricks is a plus;
• Ability to collaborate with data scientists, analysts, and business teams to understand data needs;
• Strong problem-solving skills, with the ability to troubleshoot performance bottlenecks and optimize workloads;
• Excellent communication skills to explain technical concepts to non-technical stakeholders.