Top Data Engineer Jobs in Quezon City

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.

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.

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 models, analytics pipelines, and statistical models; perform EDA and validate analyses; ensure data quality and governance; produce visualizations and reports; collaborate with analysts, engineers, and stakeholders to deliver scalable, production-ready data solutions.

Lead design and delivery of analytics, automation, and AI-enabled data solutions to improve operational efficiency across Asia Pacific. Build data pipelines, models, dashboards, desktop apps and Excel add-ins; advise stakeholders, manage projects, establish standards, and coach junior team members.

Design, develop, and maintain scalable ETL/ELT pipelines in Azure (ADF, Databricks); build and govern data models and dictionaries; integrate and ensure data quality; automate pipelines with DevOps/CICD; collaborate with data scientists, analysts and business stakeholders; perform performance tuning and capacity planning. Hybrid role with night-shift schedule.

Design, build, test, tune, and support production ETL/data pipelines using PySpark, Python, advanced SQL, and AWS data services. Implement CDC, incremental loads, idempotent processing, reconciliation, data quality checks, and maintain documentation, tests, and release support while collaborating with analysts, architects, QA, DevOps, and senior engineers.

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, develop, and maintain scalable ELT/ETL data pipelines and reusable data models using Azure Data Factory, dbt, Snowflake, SQL, and Python. Collaborate with Marketing and business stakeholders to translate requirements, ensure data quality, optimize Snowflake performance, monitor production pipelines, maintain documentation and data lineage, and mentor junior engineers.

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 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 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.

Serve as a trusted, client-facing data engineering lead for MSP customers: design, maintain and monitor automated ETL/ELT data pipelines and data infrastructure on GCP, troubleshoot and resolve platform issues, maintain data models for analytics, implement best practices, document managed-service processes, mentor junior engineers, and coordinate quarterly customer reviews and implementations.

Senior Data Engineer responsible for designing, building, and operating Enterprise Data Lake solutions. Implement ETL/ELT using Spark/Python and Azure services, monitor platform performance, perform POCs, support business users, handle incidents/changes, write documentation, execute tests and platform updates, and support agile delivery squads.

Design and implement scalable data and AI solutions. Build and optimize EL(T) pipelines, manage data extraction/integration/storage, apply software engineering best practices, mentor team members, collaborate with stakeholders, and drive AI/data platform adoption across projects.

Lead technical delivery of large-scale data platform and BI solutions: gather requirements from clients, design and implement data platforms, build ETL/ELT pipelines, perform data modelling and SQL performance tuning, provide documentation, training and knowledge transfer, and advise on profiling, integration and platform performance/cost.