Junior Data Engineer (Azure Databricks/Changi Business Park)

We are seeking a hands‑on Azure Databricks Data Engineer to support the implementation of a modern data platform on Microsoft Azure to enable self‑serve data analytics for various business users. This role is technical execution-focused, responsible for building data pipelines, implementing structured data layers, and supporting the deployment of Databricks Genie capabilities based on predefined architecture and design.

Job Description

Responsibilities:

• 1. Azure Databricks Platform Implementation
  • a) Develop and maintain data solutions using Azure Databricks (notebooks, Delta Lake)
  • b) Configure and optimize Databricks jobs, clusters, and workloads
  • c) Integrate with Azure Data Lake (ADLS Gen2)
• 2. Databricks Genie Implementation Support
  • a) Support implementation of Databricks Genie based on predefined architecture
  • b) Prepare curated datasets for Genie consumption
  • c) Optimize data structures for query performance
• 3. Data Pipeline Development
  • a) Build ETL/ELT pipelines using Databricks and Azure tools
  • b) Develop ingestion pipelines from APIs, databases, and external systems
  • c) Ensure pipelines are reliable, monitored, and production‑ready
• 4. Data Management & Governance
  • a) Apply data quality checks and controls
  • b) Implement access control and data organization practices
  • c) Document pipelines and datasets
• 5. Production Readiness & Optimization
  • a) Ensure scalability and performance
  • b) Optimize queries and pipeline efficiency
  • c) Improve Genie performance to deliver faster, more efficient results

Job requirements:

• 1. Hands‑on skills of Azure Databricks (Delta Lake, notebooks), Azure Data Lake (ADLS Gen2), Azure Data Factory or Synapse
• 2. Good SQL and ETL experience and medallion architecture familiarity
• 3. Exposure to Databricks Genie, familiarity with Python/PySpark, Unity Catalog or data governance tools are advantageous
• 4. Good execution focus with the ability to deliver high‑quality work independently
• 5. High attention to details, particularly in data quality and accuracy
• 6. Good problem‑solving skills, with the ability to troubleshoot data and pipeline issues
• 7. Receptive to feedback and able to iterate quickly based on technical guidance
• 8. Able to collaborate effectively within a technical team environment