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Databricks Data Platform Engineer/Architect
Job summary
A technology consulting firm in Abu Dhabi seeks a skilled DataBricks Platform Engineer to manage and optimize data systems. The ideal candidate will have over 10 years in IT and a deep understanding of data engineering, alongside proficiency in Python and PySpark. Key responsibilities include ensuring system performance and security, optimizing ETL processes, and providing insights into platform usage. This position offers an exciting opportunity to work at the intersection of data platforms and software engineering.
Qualifications
- Minimum 10 Years of experience in IT/Data.
- Minimum 3 years of experience as a Databricks Data Platform Engineer.
- Expertise in storage, networking, and compute on Azure or AWS.
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.
Skills
Education
Tools
Project description
We are seeking an expert with deep proficiency as a DataBricks 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.
- 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.
- 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 PostgreSQL, 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.
- Containerization & Orchestration: Docker, Kubernetes.
- Infrastructure as Code (IaC): Terraform.
- Understanding of Investment Data domain (desired).
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.