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Databricks Data Platform Engineer​/Architect

Job in Abu Dhabi, UAE/Dubai
Listing for: Luxoft
Full Time position
Listed on 2025-12-17
Job specializations:
  • IT/Tech
    Data Engineer, Cloud Computing
Salary/Wage Range or Industry Benchmark: 120000 - 200000 AED Yearly AED 120000.00 200000.00 YEAR
Job Description & How to Apply Below

Project description

We are seeking an expert with deep proficiency as a Data Bricks Platform Engineer, possessing experience in data engineering. This individual should have a comprehensive understanding of both data platforms and software engineering, enabling them to integrate the platform effectively within an IT ecosystem.

Responsibilities
  • Manage and optimize Databricks data platform.
  • Ensure high availability, security, and performance of data systems.
  • Provide valuable insights about data platform usage.
  • Optimize computing and storage for large-scale data processing.
  • Design and maintain system libraries (Python) used in ETL pipelines and platform governance.
  • Optimize ETL Processes - Enhance and tune existing ETL processes for better performance, scalability, and reliability.
SKILLS Must have
  • Minimum 10 Years of experience in IT/Data.
  • Minimum 3 years of experience as a Databricks Data Platform Engineer.
  • Bachelor's in IT or related field.
  • Infrastructure & Cloud:
    Azure, AWS (expertise in storage, networking, compute).
  • Programming:
    Proficiency in PySpark for distributed computing.
  • Proficiency in Python for ETL development.
  • SQL:
    Expertise in writing and optimizing SQL queries, preferably with experience in databases such as Postgre

    SQL, MySQL, Oracle, or Snowflake.
  • Data Warehousing:
    Experience working with data warehousing concepts and Databricks platform.
  • ETL Tools:
    Familiarity with ETL tools & processes
  • Data Modelling:
    Experience with dimensional modelling, normalization/denormalization, and schema design.
  • Version Control:
    Proficiency with version control tools like Git to manage codebases and collaborate on development.
  • Data Pipeline Monitoring:
    Familiarity with monitoring tools (e.g., Prometheus, Grafana, or custom monitoring scripts) to track pipeline performance.
  • Data Quality Tools:
    Experience implementing data validation, cleaning, and quality frameworks, ideally Monte Carlo.
Nice to have
  • Containerization & Orchestration:
    Docker, Kubernetes.
  • Infrastructure as Code (IaC):
    Terraform.
  • Understanding of Investment Data domain (desired).
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