Data Engineer

77GSI; Makati; On-site; PHP 1,000,000 - 1,800,000; Full time

Job summary

77GSI in Makati seeks an experienced Data Engineer to design and implement scalable data storage, ingestion, and transformation pipelines while emphasizing data quality and governance. You will collaborate with cross-functional teams to define data requirements and drive improvements across the data platform.

The role focuses on automating data jobs, optimizing performance, and maintaining platform stability using Databricks, Azure, SQL, Python, and PySpark.

Qualifications

• 6+ years of experience in Data Engineering or data-related projects.
• Hands-on experience with Databricks, Azure, SQL, Python, and PySpark.
• Strong background in Data Warehousing and Data Mart concepts.
• Experience designing and developing data ingestion, transformation, and integration pipelines.
• Knowledge of data governance practices and Azure DevOps familiarity.
• Experience with job automation and data platform monitoring is preferred.

Responsibilities

• Design and develop data storage solutions, including database objects, data structures, and data ingestion pipelines.
• Build and maintain data transformation, cleansing, and preparation processes.
• Optimize and automate data jobs through code enhancements, configuration improvements, and new technologies.
• Perform unit testing and system integration testing to ensure data quality and reliability.
• Monitor and maintain EDP platform stability and performance, including updates, patches, and operational enhancements.
• Ensure compliance with data governance, security policies, and SDLC standards.
• Collaborate with cross-functional teams to identify data requirements and improvement opportunities.
• Develop and maintain technical documentation for data engineering processes and procedures.
• Conduct Proof of Concepts (POCs) for new data integration and analytics solutions.
• Contribute to data engineering best practices, standards, and continuous improvement initiatives.

Skills

Databricks

Azure

SQL

Python

PySpark

Tools

Databricks

Azure

PySpark

SQL

Job description

• Design and develop data storage solutions, including database objects, data structures, and data ingestion pipelines.
• Build and maintain data transformation, cleansing, and preparation processes.
• Optimize and automate data jobs through code enhancements, configuration improvements, and new technologies.
• Perform unit testing and system integration testing to ensure data quality and reliability.
• Monitor and maintain EDP platform stability and performance, including updates, patches, and operational enhancements.
• Ensure compliance with data governance, security policies, and SDLC standards.
• Collaborate with cross-functional teams to identify data requirements and improvement opportunities.
• Develop and maintain technical documentation for data engineering processes and procedures.
• Conduct Proof of Concepts (POCs) for new data integration and analytics solutions.
• Contribute to data engineering best practices, standards, and continuous improvement initiatives.

Qualifications:

• At least 6 years of experience in Data Engineering or Data-related projects.
• Strong hands-on experience with Databricks, Azure, SQL, Python, and PySpark.
• Strong background in Data Warehousing and Data Mart concepts.
• Experience designing and developing data ingestion, transformation, and integration pipelines.
• Good understanding of data governance tools and practices.
• Familiarity with Azure DevOps.
• Experience in job automation, performance optimization, and data platform monitoring is preferred.