Senior Databricks Technical Lead

Responsibilities:

• Architect and lead Databricks Lakehouse solutions using Delta Lake, Unity Catalog, and MLflow.
• Design and develop high-volume batch and real-time pipelines using Spark (PySpark / Scala).
• Implement bronze–silver–gold data patterns, medallion architecture, and scalable data models.
• Build ingestion frameworks using ADF/ cloud-native services / Kafka / Event Hub.
• Define and enforce coding standards, performance benchmarks, and cost controls.
• Lead Databricks cluster strategy, job orchestration, and workload optimisation.
• Implement data quality checks, validation rules, reconciliation, and DQ scorecards.
• Enable metadata management, lineage, and cataloguing across enterprise datasets.
• Design secure access using RBAC/ABAC,Unity Catalog, data masking, and row/column-level security.
• Integrate CI/CD pipelines for notebooks, jobs, and infrastructure (Git, Azure DevOps, Terraform).
• Support UAT, production go-live,monitoring, and BAU stabilization.

Requirements:

• Databricks (Azure/AWS) – advanced hands-on
• Apache Spark (PySpark / Scala)
• Delta Lake, Unity Catalog, MLflow
• Cloud data services (ADF, ADLS/S3, Event Hub/Kafka)
• Data modelling (Dimensional, Analytical, Semantic Layer)
• Performance tuning, query optimisation, cost governance
• CI/CD for data platforms
• Security & compliance (PDPA/GDPR concepts)