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Databricks Data Platform Engineer

Job in Abu Dhabi, UAE/Dubai
Listing for: Epergne Solutions
Full Time position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    Data Engineer, Data Science Manager
Salary/Wage Range or Industry Benchmark: 120000 - 200000 AED Yearly AED 120000.00 200000.00 YEAR
Job Description & How to Apply Below

Overview

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.

Responsibilities
  • Key Responsibilities – Develop batch pipelines using Delta Lake with proper table design, partitioning, optimization, and lifecycle management
  • Implement incremental ingestion using Autoloader with schema evolution and checkpointing
  • Build Structured Streaming pipelines with watermarking, state management, and late data handling
  • Develop declarative pipelines using Lakeflow standards
  • Ensure pipelines support idempotency, replayability, and safe backfills
  • Optimize Spark workloads (AQE, skew handling, shuffle tuning, join optimization)
  • Build curated, analytics-ready datasets for SQL analytics and downstream consumption
  • Develop DBSQL views aligned with enterprise semantic standards
  • Implement CI/CD deployments using Repos and asset-based packaging
  • Add monitoring, logging, and operational observability to pipelines
  • Secondary Responsibilities – Ensure compliance with Unity Catalog access controls and governance policies
  • Embed data quality validations as per governance standards
  • Support migration of legacy data workloads to Databricks including validation and performance tuning
  • Collaborate with Data Ops for deployment readiness and production stability
Qualifications
  • Strong hands-on experience with Azure Databricks, Spark, and Py Spark
  • Deep knowledge of Delta Lake, Autoloader, and Structured Streaming
  • Experience with Lakeflow pipelines and DBSQL development
  • Expertise in Spark performance tuning and optimization techniques
  • Understanding of data governance, access control, and data quality frameworks
  • CI/CD and Dev Ops experience in data platform environments
  • Experience supporting production-grade data platforms
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