Data Lead – Data Engineering

Aryan Solutions • Information Technology • Python • SQL • ETL/ELT • SSIS • Azure Data Factory • 14 days ago
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Salary
$141k – $188k per year (gross)
Location
In office (Singapore)
Seniority
Staff · 7+ years exp
Employment
Full-Time

First seen by Alion on Sep 15, 2026.

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Aryan Solutions

IT solutions, four core AI products and specialist recruitment. Technology and talent, built around your business.
aryan-solutions.com • Singapore • UTC+08:00 • Information Technology
Tech stack of Aryan Solutions

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

Skills

Microsoft Sql Server Integration Services (SSIS), Control M, Spark SQL, Optimization, PySpark, Azure Monitor, ETL Tools, Data Pipeline, ETL specification, Azure Data Factory, Product Exposure, Databricks, Batch Processing, Log Analysis, Hands-On Experience, Autosys

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