Top Data Engineer Jobs in Quezon City

As a Software Engineer on the AI team at Speechify, you will manage data collection, enhance cloud infrastructure for ingestion pipelines, and collaborate on datasets for model training.

Own and operate the company's end-to-end data platform: build and run ETL/ELT pipelines, maintain a single trusted warehouse, enforce data quality, enable self-serve access, review schema changes, and lead a small data engineering team to deliver near real-time, accurate data for teams and AI tools.

The Senior Data Engineer will design and build data infrastructure and pipelines, enhance AI capabilities, and collaborate with teams on data solutions while mentoring junior engineers.

The Data Architect will design and implement data infrastructure, collaborating with teams to enhance data usage for analytics, automation, and AI, while ensuring compliance and governance.

Lead site-based CSA activities for data centre projects: manage contractors, ensure compliance with design, safety and quality, coordinate stakeholders, produce reports, and support project leadership.

Designs, develops, and maintains Power BI dashboards, semantic/data models, and reporting datasets. Uses SQL and DAX to transform and validate enterprise data, partners with stakeholders to define KPIs, troubleshoots BI solutions, and contributes to governance and continuous improvement across GBS finance and operations.

Build and operate AWS serverless infrastructure and data pipelines, design integrations across accounting and business apps, develop and test LLM-based financial agents, lead client discovery sessions, and document and standardize platform and agent implementations to maintain security and compliance.

Design, code, and maintain SQL procedures; troubleshoot database issues; review SQL code; create SSIS packages; perform data analysis and profiling.

Develop, deploy, and maintain LLM pipelines and RAG QA/search systems; design and optimize prompts and multi-agent LLM architectures; operate multi‑GPU/cluster inference; build evaluation pipelines for model quality, bias, and hallucination; collaborate with product and CS teams to integrate conversational AI.

Lead Data Engineer to design, build, and maintain scalable ETL pipelines and cloud data platforms, optimize data models/warehouses, ensure data quality and governance, and collaborate with analytics and business teams.

Monitor daily data intake across channels, perform QA to detect inconsistencies or unusual trends, troubleshoot ingestion issues, document findings, and propose process/product improvements while working scheduled shifts.

Operate, monitor and improve production DataOps/ETL workloads for SLHK: manage enterprise schedules and SLAs, lead incident response, execute controlled changes, run data quality checks with evidence, maintain runbooks, and publish/automate service reporting.

Design, develop, and maintain data solutions and applications, ensuring data quality and performance while collaborating with cross-functional teams.

Hands-on APAC-focused database engineer responsible for administering and optimizing enterprise Oracle and multi-database platforms across OCI and AWS. Duties include migrations, patching, backup/recovery, HA/DR, performance tuning, automation (IaC/CI-CD), monitoring, incident resolution, and collaboration with global teams to ensure service reliability and operational excellence.

Lead design and optimization of scalable ETL/data pipelines across on-premise and cloud environments, implement Microsoft Fabric solutions, build Power BI reports and unified data models, manage integrations and migrations (including Dynamics/Dataverse), ensure data quality/security/governance, troubleshoot and automate workflows, engage customers for requirements and delivery, and mentor team members.

Lead design, implementation and optimization of data infrastructure and scalable ETL pipelines across Microsoft Fabric, on-premise SQL, and Dynamics 365. Ensure data quality, governance, security, and unified data models. Build Power BI dashboards and analytical models, manage migrations and integrations, troubleshoot complex issues, document solutions, mentor team members, and drive platform adoption and best practices.

Manage and maintain data operations infrastructure and pipelines: design databases and ETL, ensure data quality, automate ingestion/transformation using SQL and Python, troubleshoot issues, collaborate with data teams, and integrate sources like Oracle, JDE, SharePoint, Excel, and SAP to produce usable data products.

The Cloud Data Test Engineer will test cloud-based data solutions, ensure data pipeline quality, perform end-to-end data validation, and create test plans.

Hands-on senior data engineer role building and operating client-specific ELT pipelines and three-layer dbt projects on cloud warehouses (pref. BigQuery). Own pipeline operations, reconciliation and testing, semantic layer/metric definitions (Cube.dev), freshness/anomaly monitoring, PII-aware quality frameworks, and translate client domain discovery into reliable business marts to power dashboards and AI queries.

Own quality for the Data Platform and Analytics products by validating pipelines, warehouse models, and reports. Write SQL to reconcile reports with raw sources and upstream APIs, build automated data quality checks (Soda), test Airflow DAGs and Databricks jobs, develop API tests for REST/GraphQL, and collaborate with Engineering, Product, and Analytics to document findings and prevent defects.