Top Data Engineer Jobs in the Philippines

Design, build, and maintain data storage, ingestion and transformation pipelines. Optimize jobs, automate processes, perform unit and integration testing, monitor platform stability, ensure governance and security compliance, collaborate with stakeholders, document processes, run POCs, and contribute to team best practices to support analytics and data engineering needs.

Support design, develop, test and deploy ETL/ELT pipelines for Finance data lake and warehouse. Provide L1/L2 platform support, implement data quality, validation and governance, maintain metadata/lineage, and collaborate with business users and analysts to translate requirements and enable BI self-service.

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, 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.

Design and maintain secure data platforms, optimize data workflows and processes, and collaborate with stakeholders to implement data solutions.

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

Design, build, and maintain end-to-end data pipelines and AWS infrastructure to support trade and communications surveillance. Implement automated data quality/completeness checks, reconciliation, lineage, retention, testing, monitoring, and recovery. Collaborate with stakeholders, compliance, and cloud teams to ensure regulatory, security, and performance requirements are met for structured and unstructured surveillance data.

Build, scale, and maintain end-to-end batch and streaming ETL/ELT pipelines on Databricks/Spark over AWS. Shape lakehouse architecture on S3/Delta Lake, optimize Spark performance, manage Databricks workflows and clusters, implement Unity Catalog governance, and ensure data correctness for analytics and product teams.

Design, develop, optimize, and maintain ETL/data integration processes using IBM DataStage and Oracle Database 19c. Build and tune complex SQL queries, perform data validation, troubleshoot and support scheduled ETL jobs, and ensure data quality and reliability in production environments.

Design, implement, and maintain scalable data infrastructure for analytics and operational decision-making, optimizing data pipelines and ensuring data quality.

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

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, build, and maintain data pipelines and databases to support actuarial analytics. Perform data manipulation with SQL/Python, ensure data quality, document sources, automate ingestion and transformations, and collaborate across teams to optimize data architecture and processes.

Build and maintain data pipelines and databases to enable analytics-driven decision making. Develop ETL/ELT processes using SQL and Python, design dimensional models, automate ingestion and orchestration (Airflow), evaluate data quality, document sources, and collaborate cross-functionally to improve processes and support actuarial analytics.

Design, build, and maintain end-to-end analytics and reporting solutions: ingest, transform, model, and store data; build Cognos and Power BI reports; ensure data quality; analyze datasets and present insights to stakeholders.

Design, build, and maintain Microsoft Fabric data architectures and ETL pipelines (Fabric, Synapse, ADF). Transform and optimize data for analytics and AI, support RAG/LLM workloads, ensure data quality, governance, performance, and document workflows.

Responsible for developing and maintaining ELT snowflake solutions, collaborating with teams, mentoring developers, and improving data engineering practices.

Data Engineer II will execute data project initiatives, maintain data applications, automate processes, and mentor junior developers while collaborating with teams.

Design, build, and maintain scalable ETL and real-time data processing systems on Databricks and AWS. Develop Spark-based pipelines, ensure data quality and governance, implement security controls, automate infrastructure with Terraform, and collaborate with analysts and engineers to resolve issues and optimize performance.

Design, build, test and maintain ETL pipelines using Python and Jupyter notebooks. Transform vendor and client data, migrate Excel logic to Python, document processes, respond to incidents within SLAs, automate processes, and collaborate with business and technical teams to improve data workflows.

Design, build, and maintain scalable Azure-based data pipelines, ETL/ELT processes, data warehouses, and reusable data services. Provide Level 2/3 support for data platforms, troubleshoot production incidents and data quality issues, implement CI/CD and DevOps automation, and collaborate with business and engineering teams to deliver governed analytics solutions.

The Data Engineer Consultant captures, transforms, and loads data using Azure services, ensuring data quality and developing ETL pipelines while collaborating with stakeholders.

Build and maintain cloud-based data pipelines and architectures using SQL and Python. Collaborate with modelers to assemble large datasets, automate and optimize ETL processes, ensure data quality, document technical solutions, and explore new data sources to support predictive analytics.

The Data Engineer will design, develop, and maintain data pipelines and architecture, ensuring data quality and governance, while collaborating with data professionals.