Data Engineer
Summary
A data engineer in Mandaluyong City who designs, builds, and maintains scalable data pipelines, ETL/ELT processes, and data warehouses/lakes. Day to day involves ensuring data quality and governance, automating workflows, and delivering analytics-ready datasets for data scientists, analysts, and business stakeholders.
Salary: ₱70,000 – ₱85,000 per month
About the role
Roles and ResponsibilitiesData Pipeline & Infrastructure Development
Design, build, and maintain scalable data pipelines for ingestion, transformation, and storage.
Develop and manage ETL/ELT processes to integrate data from various internal and external sources.
Build and maintain data warehouses, data lakes, and hybrid data storage solutions.
Monitor, optimize, and enhance pipeline performance, reliability, and cost efficiency.
Data Quality & Reliability
Implement data validation, quality checks, and monitoring frameworks.
Investigate and resolve data issues, anomalies, and pipeline failures.
Ensure data accuracy, completeness, and consistency across all systems.
Continuously improve data reliability and availability.
Collaboration & Analytics Enablement
Work closely with data scientists, analysts, and business stakeholders to understand data requirements.
Provide curated, analytics-ready datasets for reporting, dashboards, and advanced analytics.
Collaborate with Data Architects and Enterprise Architecture teams to align with organizational standards.
Data Security & Governance Support
Ensure data solutions comply with governance, security, and privacy policies.
Implement access controls, data masking, and other security measures as needed.
Support metadata management, documentation, and data lineage tracking.
Documentation & Automation
Develop and maintain documentation, including data flow diagrams, pipeline designs, and data dictionaries.
Automate data processing and operational workflows to minimize manual effort and errors.
Document procedures and troubleshooting guidelines.
Technology Evaluation & Continuous Improvement
Assess and adopt emerging data tools, platforms, and engineering best practices.
Stay updated with trends in big data, cloud technologies, and data engineering frameworks.
Recommend enhancements to improve data infrastructure and processing efficiency.
Requirements
Bachelor’s degree in Computer Science, Information Technology, or a related field.
At least 2 years of relevant experience in data engineering or a similar role.
Hands-on experience with ETL processes and data warehousing solutions.