Job Role
:-Databricks Data Platform Engineer
Job Location
:-Abu Dhabi, UAE
Experience
:-5+ Years
Role Summary
Design and build scalable, high-performance, and governed data pipelines on Azure Databricks to support analytics, reporting, and enterprise data intelligence initiatives.
Key Responsibilities
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Develop batch pipelines using Delta Lake with proper table design, partitioning, optimization, and lifecycle management
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Implement incremental ingestion using Autoloader with schema evolution and checkpointing
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Build Structured Streaming pipelines with watermarking, state management, and late data handling
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Develop declarative pipelines using Lakeflow standards
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Ensure pipelines support idempotency, replayability, and safe backfills
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Optimize Spark workloads (AQE, skew handling, shuffle tuning, join optimization)
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Build curated, analytics-ready datasets for SQL analytics and downstream consumption
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Develop DBSQL views aligned with enterprise semantic standards
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Implement CI/CD deployments using Repos and asset-based packaging
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Add monitoring, logging, and operational observability to pipelines
Secondary Responsibilities
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Ensure compliance with Unity Catalog access controls and governance policies
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Embed data quality validations as per governance standards
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Support migration of legacy data workloads to Databricks including validation and performance tuning
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Collaborate with DataOps for deployment readiness and production stability
Required Skills & Experience
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Strong hands-on experience with Azure Databricks, Spark, and PySpark
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Deep knowledge of Delta Lake, Autoloader, and Structured Streaming
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Experience with Lakeflow pipelines and DBSQL development
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Expertise in Spark performance tuning and optimization techniques
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Understanding of data governance, access control, and data quality frameworks
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CI/CD and DevOps experience in data platform environments
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Experience supporting production-grade data platforms