25 Data Engineer jobs in Philippines available for remote work from home. Apply for positions such as Data Engineer, Data Engineer (SnowFlake), Data Engineer – MDM, Cloud Data & Analytics (International Hiring) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Build and maintain scalable, reliable data pipelines and govern performant cloud-deployed relational and non-relational databases. Collaborate on secure architecture definitions to drive data systems toward near real-time performance.
The Data Engineer will provide Level 2 and Level 3 support for Snowflake-based data platforms, ensuring platform availability and performance. They will also investigate incidents, perform root cause analysis, and implement permanent fixes to maintain service stability and operational excellence.
Design, develop, and maintain enterprise-scale data solutions including MDM, cloud data platforms, and analytics engineering. Collaborate with cross-functional teams to build secure, scalable data pipelines and interactive business intelligence dashboards.
Design, develop, and maintain enterprise-scale data solutions including Master Data Management, cloud data platforms, and analytics. Collaborate with cross-functional teams to build scalable, secure, and reliable data pipelines and business intelligence dashboards.
You will lead the frontend and data modeling layer by transforming raw GCP data into actionable insights for clients. The role involves managing a complex, multi-tenant Looker environment to ensure secure, scalable, and high-performance dashboard architecture.
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The role involves managing data collection and ingestion pipelines to support AI model training at scale. You will collaborate with scientists and leadership to optimize data infrastructure and define the dataset roadmap for consumer and enterprise products.
The role involves designing, building, and maintaining scalable ETL/ELT pipelines within Snowflake to support analytics and AI-driven business capabilities. You will also manage data transformation workflows, ensure data quality, and collaborate with cross-functional stakeholders to deliver reliable data solutions.
The Data Engineer will collect, process, and clean data while designing ETL pipelines and automation workflows to support business decisions. They will also conduct in-depth data analysis, build predictive models, and develop visualizations using BI tools to provide actionable insights to clients.
Design, build, and maintain scalable cloud-native data platforms and robust ELT/ETL pipelines using Snowflake. Partner with stakeholders to enable self-service analytics while ensuring data quality, governance, and performance optimization.
The Senior QA Engineer will ensure the accuracy of data pipelines, warehouse models, and analytics reports by validating metrics against raw source data. They will also design and implement automated data quality checks and test platform infrastructure including Airflow DAGs and Databricks jobs.
Design and operate AWS cloud infrastructure and data pipelines to support AI-powered financial systems. Lead technical discovery sessions with clients to translate business needs into automated AI agent workflows.
The role involves building and operating end-to-end data pipelines and dbt projects to transform raw source systems into governed data marts. You will collaborate with client stakeholders to translate business logic into metric definitions and ensure data quality for AI agents and executive dashboards.
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Design, build, and maintain robust ETL/ELT data pipelines and infrastructure on Google Cloud Platform to power company analytics. Collaborate with stakeholders to deliver reliable data models and manage workflow orchestration using Apache Airflow.
Design, build, and maintain robust ETL/ELT data pipelines and infrastructure on Google Cloud Platform to power company analytics. Collaborate with stakeholders to deliver reliable data models and manage workflow orchestration using Apache Airflow.
Design, build, and scale modern cloud-based data platforms with a primary focus on Snowflake architecture and performance. Develop robust ELT/ETL pipelines and curated data models to enable trusted analytics and self-service reporting across the organization.
The Lead Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and platforms to support business operations. This includes optimizing data models, ensuring data governance, and collaborating with analytics teams to meet data requirements.
The Senior Data Storage and Backup Engineer manages the full lifecycle of enterprise storage and backup infrastructure, including design, implementation, and troubleshooting. This role ensures data availability and integrity while collaborating with internal stakeholders to optimize performance and automate operational tasks.
Design and implement a BigQuery-based medallion architecture and data ingestion pipelines from various GCP sources. Provide technical documentation and collaborate with cross-functional teams to support AI enrichment and BI-ready datasets.
This role involves extending and expanding technical leadership knowledge through technical decision-making, guiding junior team members, and developing client relationships, all while remaining hands-on in areas of expertise focused on the Azure technology stack. The position requires designing and implementing data architectures for various data formats in cloud and hybrid environments, utilizing expertise in data modeling and Azure Data Platform services.
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