Top Data Engineer Jobs in Manila

Design, build, and maintain scalable back-end services and front-end applications; implement RESTful APIs and microservices; contribute to ETL, data pipelines, and data modeling; optimize performance and security; mentor engineers; promote CI/CD and engineering best practices while collaborating with product and global 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.

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

Design, develop, and maintain complex T-SQL stored procedures and SSIS ETL packages; performance tune databases; perform data analysis, validation, and testing; support production data loads and troubleshoot database issues while collaborating with technical and business teams.

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

Develop, test, and maintain enterprise applications and services; build APIs and system integrations; collaborate with business and technical teams in Agile; troubleshoot defects and performance issues; maintain documentation and support deployments.

Develop, test, and maintain enterprise applications and services; support API development and system integrations; collaborate with business and technical teams in Agile; troubleshoot defects and performance issues; maintain documentation and support deployments.

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.

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.

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.

Design, build, and maintain scalable ETL/ELT pipelines and data architecture; integrate multiple data sources; ensure data quality, governance, security, and performance; monitor pipelines; support BI, analytics, and ML; document models and workflows; collaborate with stakeholders.

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.

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.