Top Data Engineer Jobs in the Philippines

As a Data Engineer, you will design and maintain data solutions using Azure and Databricks, implementing ETL processes and optimizing data pipelines.

Provide technical leadership and mentorship to software engineering teams, collaborate cross-functionally to define requirements, manage project tasks/timelines/budgets, identify and mitigate risks, participate in strategy and technology assessments, and promote a culture of innovation and continuous learning.

Lead applications business development, account management, and service delivery for large accounts. Develop operational plans and budgets, resolve staffing and client issues, grow accounts through strategy and solutions, hire and coach staff, ensure contract compliance and client satisfaction, and collaborate on delivery models and financial targets.

Design, build, and maintain scalable data pipelines and ETL processes using Python and SQL. Optimize schemas and queries, deploy/manage data workloads on AWS, and collaborate with analysts and business teams to ensure data accuracy, availability, and governance.

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.

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

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.

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

Design, build, deploy, and maintain data processing applications and infrastructure; perform ETL, monitor production, resolve incidents, support stakeholders, and create proofs-of-concept and documentation.

Design, build, and maintain ETL/ELT data pipelines and ingestion processes to produce analyst-ready datasets. Collaborate with stakeholders to translate business logic into documented, testable data assets, improve workflows via API integration, automation, and AI, and follow data and AI governance standards.

Design, build, and optimize ETL/ELT pipelines to replicate and transform production MongoDB data into Google BigQuery. Maintain BI integration (Looker Studio), optimize BigQuery performance and costs, implement safeguards to protect production databases, and develop MERN/TypeScript backend tools for automated data workflows while enforcing data governance and privacy.

Design and implement BigQuery-based medallion (lakehouse) architectures and ingestion pipelines on GCP; define datasets, partitioning, clustering, and cost controls; support batch/incremental/on-demand processing; implement data quality, monitoring, and search/AI integration; produce architecture docs and work with engineering, data, DevOps, and product teams for handover.

The Data Engineer will design, develop, and maintain data pipelines, ensuring accurate data for reporting and decision-making, while improving internal processes and keeping up with technology trends.

Support pre- and post-deployment data pipeline and product integration activities. Assist clients with data ingestion and configurations, monitor and maintain pipelines (e.g., Matillion), troubleshoot scripts and integration issues (PHP, Postgres), document procedures, and escalate complex problems to senior engineers while collaborating with support and product teams.

Intern will support and develop features in a web project, applying data cleansing and implementing visualizations for customers.

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.

Design, develop, and maintain data pipelines and workflows (batch/streaming), ensure data quality and governance, write clean tested code, troubleshoot processing issues, collaborate in agile teams, produce documentation, and support deployments while growing technical skills under senior guidance.

Design, build, and maintain scalable data pipelines and storage on cloud platforms. Implement ETL, data models, data quality monitoring, governance, and collaborate with data scientists for analytics and reporting.

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

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.