Data Engineer
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Summary
Designs, builds, and maintains scalable data pipelines and ETL processes on Azure for a Singapore-based team, working daily with Azure Synapse Analytics, Data Factory, ADLS Gen2, Logic Apps, and PySpark to integrate, transform, and optimize large datasets.
Job Role
: -Data Engineer
Job Location
: -Singapore
Experience
: -4-8 Years
Roles & Responsibilities: - Design, develop, and maintain scalable data pipelines and ETL processes on Azure Cloud. Work with Azure Synapse Analytics, Azure Data Factory, and ADLS Gen2 to integrate, transform, and manage large datasets. Develop and optimize PySpark scripts for distributed data processing and analytics. Implement and manage Azure Logic Apps for workflow automation and data integration tasks. Collaborate with cross-functional teams to understand business requirements and deliver efficient data solutions. Monitor, troubleshoot, and optimize performance of data pipelines and storage systems. Ensure data quality, consistency, and security across all platforms. Document processes, data flows, and technical solutions for operational transparency. Support the implementation of best practices in data engineering, cloud architecture, and automation.
Skills & Requirements: - Hands-on experience with Azure Synapse Analytics, Azure Logic Apps, Azure Data Lake Storage (ADLS Gen2). Strong experience in PySpark, Azure Data Factory, and SQL-based data transformations. Solid understanding of cloud data architectures, distributed processing, and ETL design patterns. Strong problem-solving, analytical, and communication skills. Self-motivated, proactive, and able to make independent decisions within a collaborative team environment. Good to Have: Experience with Databricks or other big data processing platforms. Knowledge of data governance, monitoring, and performance tuning in cloud data environments.
: -Data Engineer
Job Location
: -Singapore
Experience
: -4-8 Years
Roles & Responsibilities: - Design, develop, and maintain scalable data pipelines and ETL processes on Azure Cloud. Work with Azure Synapse Analytics, Azure Data Factory, and ADLS Gen2 to integrate, transform, and manage large datasets. Develop and optimize PySpark scripts for distributed data processing and analytics. Implement and manage Azure Logic Apps for workflow automation and data integration tasks. Collaborate with cross-functional teams to understand business requirements and deliver efficient data solutions. Monitor, troubleshoot, and optimize performance of data pipelines and storage systems. Ensure data quality, consistency, and security across all platforms. Document processes, data flows, and technical solutions for operational transparency. Support the implementation of best practices in data engineering, cloud architecture, and automation.
Skills & Requirements: - Hands-on experience with Azure Synapse Analytics, Azure Logic Apps, Azure Data Lake Storage (ADLS Gen2). Strong experience in PySpark, Azure Data Factory, and SQL-based data transformations. Solid understanding of cloud data architectures, distributed processing, and ETL design patterns. Strong problem-solving, analytical, and communication skills. Self-motivated, proactive, and able to make independent decisions within a collaborative team environment. Good to Have: Experience with Databricks or other big data processing platforms. Knowledge of data governance, monitoring, and performance tuning in cloud data environments.