Data Lead Data Engineering

aryan solutions pte. ltd.; Singapore; On-site; SGD 150,000 - 210,000; Full time

Job summary

aryan solutions pte. ltd. is seeking a Data Lead - Data Engineering to drive diagnostics, optimisation, and stabilisation of enterprise data platforms supporting large-scale ETL and batch processing.

You will lead design and operation of pipelines using ADF, Databricks, and SSIS, manage scheduling with Control-M/Autosys, and ensure data quality and performance while collaborating with data engineers and business teams to deliver reliable production systems.

Qualifications

• Strong experience with Azure Data Factory, Databricks, SSIS and SQL Server.
• Hands-on batch orchestration using Control-M or Autosys.
• Proficient in SQL development and performance tuning.
• Familiarity with monitoring tools like Azure Monitor and Log Analytics.
• Experience with large-scale data processing and batch systems.
• Ability to review and optimize ADF pipelines, SSIS packages, and Databricks workflows.
• Experience analyzing batch scheduling, dependencies, triggers, and SLAs.
• Ability to troubleshoot pipeline failures and ensure faster recovery.
• Experience with data quality, error handling, and retry strategies across ETL and batch processes.
• Knowledge of data modernization from legacy ETL to cloud platforms.

Responsibilities

• Drive diagnostics, optimisation, and stabilisation of enterprise data platforms.
• Lead design and operation of ETL/ELT pipelines for large-scale data.
• Improve error handling, retries, restarts, and reprocessing strategies.
• Optimize runtime performance of data pipelines and batch jobs.
• Establish monitoring and alerting frameworks using Azure Monitor and dashboards.
• Collaborate with data engineers, architects, and business teams to deliver reliable production systems.
• Identify automation opportunities to reduce manual interventions.

Skills

ADF

Databricks

SSIS

SQL Server

Batch orchestration

ETL/ELT design

SQL development

Monitoring

Azure Monitor

Control-M

Autosys

Data quality

cloud data platforms

troubleshooting

automation opportunities

Tools

Databricks

Azure Data Factory (ADF)

SSIS

Control-M

Autosys

SQL Server

Azure Monitor

Job description

Experience:7-12 Years
Location:Singapore

Fulltime Permanent Role

We are looking for a Data Lead - Data Engineeringto 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 workflowsfor 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 layersfor efficiency and correctness
• Define and improve error handling, retry mechanisms, restart ability, and reprocessing strategiesacross ETL and batch
• Optimize runtime performance of data pipelines, including query tuning and batch execution improvements
• Establish and enhance monitoring and alerting frameworksusing tools like Azure Monitor, Control-M dashboards, and custom logging solutions
• Identify automation opportunitiesto reduce manual intervention and improve operational efficiency
• Ensure data quality, consistency, and reliabilityacross 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 teamsto drive improvements and ensure stable production systems