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Azure Data Engineer | Databricks & PySpark

Full-time

Techforce Group Limited

About the Role

TechForce is partnering with a leading insurer to support their growing Data & AI team. 

Based in Manila, you'll work alongside senior engineering, architecture and analytics teams across Asia and Canada to build scalable data pipelines, reusable data products and enterprise-grade data solutions. This is an opportunity to work on a high-profile cloud data platform using Azure, Databricks and Spark technologies, supporting business, analytics and reporting use cases across a complex regional environment.

Responsibilities
  • Design, develop and support data pipelines integrating data from multiple source systems into a centralised enterprise data lake.

  • Build and maintain ETL/ELT solutions using Azure Data Factory, Azure Databricks, Spark/PySpark, Python and SQL.

  • Develop ingestion, transformation and data quality processes, leveraging established global frameworks, engineering standards and reusable patterns.

  • Troubleshoot pipeline failures, optimise processing performance and support production issue resolution.

  • Perform testing, deployment validation and data reconciliation activities to ensure reliable delivery.

  • Collaborate with architects, analysts, QA teams and engineers across Asia and North America throughout the delivery lifecycle.

  • Contribute to reusable data products and curated datasets that support reporting, analytics and business consumption.

  • Maintain technical documentation, operational procedures and knowledge-sharing materials.

Requirements
  • Strong hands-on Spark/PySpark, Python and SQL experience , with the ability to build, troubleshoot and optimise data pipelines in a production environment.

  • Practical Azure and Databricks delivery experience , including Azure Data Factory, Azure Databricks and Azure Data Lake Storage.

  • Experience delivering end-to-end data engineering solutions , including testing, data quality validation, troubleshooting, documentation and production support.

  • Experience with ETL/ELT development, data integration, transformation and large-scale data processing.

  • Strong written and spoken English with the ability to collaborate effectively across distributed regional and global teams.

  • 3+ years of relevant Data Engineering experience within cloud or enterprise data environments.

Vacancy posted 13 hours ago
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