全职 Data Lead – Data Engineering 工作, 薪水 up to SGD 15,000, ARYAN SOLUTIONS PTE. LTD. Islandwide (Singapore) 公司招聘中 - Ricebowl

Experience: 7–12 Years
Location: Singapore

Fulltime Permanent Role

We are looking for a Data Lead – Data Engineering to drive technical diagnostics, optimisation, and stabilisation of enterprise data platforms supporting large-scale ETL and batch processing systems.

Key Responsibilities

• Strong expertise in: Azure Data Factory (ADF),Databricks (PySpark / Spark SQL preferred),SSIS and SQL Server
• Hands-on experience with: Batch orchestration tools (Control-M / Autosys),ETL/ELT pipeline design and optimization
• Strong experience in: SQL development and performance tuning, Troubleshooting and debugging complex data pipelines
• Familiarity with: Monitoring and alerting tools (Azure Monitor, Log Analytics)
• Exposure to large-scale data processing and batch system
• Review and optimize ADF pipelines, SSIS packages, and Databricks workflows for performance, scalability, and 
• Analyze batch scheduling and orchestration frameworks (Control-M / Autosys), including dependencies, triggers, and SLA adherence 
• Investigate and resolve pipeline failures, job delays, and runtime issues, ensuring faster recovery and minimal business 
• Evaluate source-to-target integration flows, SQL logic, and transformation layers for efficiency and correctness 
• Define and improve error handling, retry mechanisms, restart ability, and reprocessing strategies across ETL and batch 
• Optimize runtime performance of data pipelines, including query tuning and batch execution improvements 
• Establish and enhance monitoring and alerting frameworks using tools like Azure Monitor, Control-M dashboards, and custom logging solutions  
• Identify automation opportunities to reduce manual intervention and improve operational efficiency 
• Ensure data quality, consistency, and reliability across ETL processes and reporting outputs  
• Support modernization initiatives, including migration from legacy ETL (SSIS) to cloud-based platforms like Databricks 
• Collaborate with data engineers, architects, business, and support teams to drive improvements and ensure stable production systems