Top Data Engineer Jobs in the Philippines

The Data Engineer will implement and maintain data workflows, manage ETL/ELT processes, design storage solutions, and ensure quality outputs through testing. Responsibilities include documenting specifications, collaborating with operations teams, and improving data handling processes across cloud platforms.

Maintain, clean, and normalize customer and operational data; build and sustain reliable data pipelines and analytics-ready tables. Implement basic data quality checks, monitor and resolve pipeline issues, document datasets, and support analysts and stakeholders with accurate, usable data.

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

Design, develop, and maintain ETL/data pipelines and data models for BI consumption. Configure and automate data integration jobs, perform testing and validation, monitor performance and data quality, troubleshoot issues, and collaborate with stakeholders to deliver and enhance BI datasets and platforms.

The Data Engineer will monitor and support data pipelines, troubleshoot issues, optimize SQL queries, maintain SSIS packages, and assist in Azure services operations.

Support the Marketing Data Engineering function by monitoring data ingestion jobs, validating delivery, performing compliance checks, maintaining documentation, and troubleshooting issues.

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, 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 optimize data infrastructure for reporting and analytics. Manage data synchronization, optimize BigQuery performance, enforce data security, and develop data integration tools using the MERN stack.

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.

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

The Data Engineer will build and manage data infrastructure on AWS, optimizing data pipelines and operations using AI technologies to support Guidewire's insurance products.

The Associate Data Engineer at NICE CXone supports data product infrastructure, coordinates release operations, monitors Snowflake environments, and improves DataOps processes through automation and tooling.

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.

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

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 role involves designing and building data infrastructure, developing ETL/ELT applications, collaborating with teams, and improving engineering processes for analytics and AI capabilities.

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.