Top Data Engineer Jobs in Manila

The role involves building and maintaining data pipelines, developing ETL components, testing, CI/CD deployment, and collaborating with the BA and Scrum Master on projects.

The Data Engineer will analyze raw data, build data systems, enhance data quality, develop tools, and meet business objectives.

The Data Engineer will build data systems, evaluate business needs, enhance data quality, and develop analytical tools while managing raw data.

The Data Engineer will analyze raw data, build data systems, enhance data quality, evaluate business needs, and develop analytical tools.

The Data Engineer will analyze raw data, build data pipelines, evaluate business needs, enhance data quality, and develop analytical tools.

The Data Engineer will analyze and organize raw data, build data systems and pipelines, and improve data quality for business needs.

The Data Engineer will analyze and organize raw data, build systems and pipelines, and develop analytical tools to enhance data quality.

The Data Developer will design, expand, and optimize data pipelines, process data from various sources, and assist with data-related issues.

Design, build and optimize complex Azure-based data pipelines and ETL solutions using Informatica and big-data technologies. Analyze sources, resolve data quality issues, implement automation, tune performance, and mentor junior team members to deliver end-to-end BI and real-time analytics solutions.

The Junior Data Engineer will support data integrations and master data management, ensuring clean data flows across various systems and collaborating with engineering teams.

The Data Engineer develops and manages the Manufacturing Data Lake, optimizing data pipelines, supporting CI/CD processes, and collaborating with IT and business teams.

The Data Engineer will develop and operate a cloud-based Manufacturing Data Lake, manage data pipelines, optimize solutions, and ensure efficient platform use for users.

Design and maintain a secure data platform focusing on data processing, ETL processes, and collaboration with cross-functional teams to deliver data solutions.

The SME, Data Engineer leads a team in developing data solutions, conducting POCs, and ensuring data governance and performance across platforms.

Design and develop data pipelines for data ingestion into the warehouse, ensuring data quality and optimizing existing pipelines while adhering to engineering standards.

Design and implement AI solutions, develop data architecture using Python and Django, manage databases, and collaborate with teams to enhance the platform.

The role requires integration and management of data systems, leadership in knowledge management, and collaboration with stakeholders to enhance data-driven decisions.

As a BI Data Engineer, you will focus on advanced data modeling, ETL management, database oversight, and collaborating with teams to generate insights and enhance data integrity.

The Data Engineer will develop ETL processes, maintain data pipelines, perform troubleshooting, and ensure scalable data architecture.

The Data Engineer will develop advanced PowerBI reports, optimize SQL queries, collaborate with stakeholders for reporting requirements, and ensure data accuracy across reporting solutions.

The Data Engineer will design, build, and maintain scalable data solutions, focusing on data pipelines, ETL/ELT processes, and cloud platforms, particularly Snowflake.

The Cloud Data Engineer designs, builds and maintains scalable data pipelines, implements big data storage formats, and integrates data solutions on AWS with Python, ensuring reliability and scalability.

As a Data Engineer, you will analyze information needs, design and deploy data processing applications, maintain infrastructure, and resolve incidents in production while supporting internal staff and stakeholders.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

Design, develop, and maintain data pipelines, ETL/ELT processes, and data warehouses. Build data marts and models, optimize SQL for large-scale processing, monitor and tune databases, evaluate tools, document solutions, and support analytics/reporting environments.