Top Data Engineer Jobs in Caloocan

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.

The candidate will process client reports, streamline workflows, support teams with data analytics, and develop data expertise for informed decisions.

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

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 and organize raw data, build data systems and pipelines, and improve data quality for business needs.

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 systems and pipelines, and develop analytical tools to enhance data quality.

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 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.

The Data Engineer will develop and optimize data architecture, build ETL systems, support data initiatives, and deploy data science models.

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

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

As a Data Engineer, you'll build and maintain data systems, enhance data quality, implement workflows, and communicate technical information to non-technical stakeholders.

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

The Data Engineer builds and maintains data infrastructure to enable analytics and insights across the organization, ensuring data quality and performance.

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

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

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.

The Senior Backend Engineer designs and builds automated solutions for regulatory reporting, focusing on finance and risk datasets, and collaborates with Business Analysts. Responsibilities include coding, mentoring developers, ensuring system performance, and maintaining software standards.