Cloud Engineer (Data Engineering Focus)
Summary
Build and maintain scalable Azure data pipelines (batch & real-time) using Python, PySpark, and Azure services like Synapse and Databricks to power analytics and ML.
Job Overview
Design and deliver scalable, secure, and high-performance data pipelines on Azure, enabling real-time and batch data processing to support analytics, reporting, and machine learning & relevant cloud certifications.
Key Responsibilities
- Build and maintain robust, scalable data pipelines (batch & real-time)
- Manage and optimize Azure cloud data platforms
- Ensure data quality, validation, lineage, and governance
- Implement automation, monitoring, and performance tuning
- Collaborate with Data Scientists, Analysts, and Business teams
- Provide L2/L3 support for data-related issues
- Contribute to continuous improvement and best practices
Required Certifications (Mandatory)
At least one of the following certifications is required:
- AWS Certified Solutions Architect (Associate/Professional)
- Microsoft Certified: Azure Administrator Associate or Azure Solutions Architect Expert
- Google Professional Cloud Engineer
Core Technical Skills
- Cloud (Azure): Data Factory, Synapse, Databricks, Microsoft Fabric
- Programming: Python, PySpark (Scala advantageous)
- Data Pipelines: ETL/ELT, batch and streaming architectures
- Streaming Tech: Kafka, Azure Event Hub
- Databases: SQL, Data Warehousing concepts (DB2/Netezza advantageous)
- DataOps: CI/CD pipelines, orchestration (e.g., Airflow or similar)
- Infrastructure as Code: Terraform / ARM templates (preferred)
- APIs: Exposure to building/consuming data services
Application Notice
Should you not receive any feedback within three (3) weeks of submitting your application, please consider your application unsuccessful.