Azure Data Engineer | Databricks & PySpark
Azure Data Engineer based in Manila building and supporting ETL/ELT pipelines for a large-scale enterprise data lake programme, using Azure Data Factory, Databricks, Spark/PySpark, Python and SQL, and collaborating with teams across Asia and North America.
- Compensation
- ₱90K–₱120K / mo
- Location
- Metro Manila
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 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 ability to collaborate across distributed regional and global teams
- 3+ years of relevant Data Engineering experience within cloud or enterprise data environments
Full description
Salary: ₱90,000 – ₱120,000 per month
About the Role
Join a newly expanding regional data engineering team delivering a large-scale enterprise data lake programme across multiple Asia markets.
Based in Manila, you'll work alongside senior engineering, architecture and analytics teams across Asia and North America 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.