Senior Data Quality Engineer & ML Anomaly Lead

Globe Telecom; Philippines; On-site; PHP 2,000,000 - 3,500,000; Full time

Job summary

Globe Telecom in the Philippines seeks a Data Quality Lead Expert to own the design, engineering, and continuous improvement of the Data Quality Framework. You will personally engineer complex checks and define patterns used across the data platform.

You will lead through technical excellence, build dashboards, monitor data health, and align data quality with governance, compliance, and business KPIs, while remaining an individual contributor.

Qualifications

• Experience designing and implementing data quality checks across large data platforms.
• Strong knowledge of statistical and ML-based anomaly detection methods.
• Experience with data governance, security, and compliance controls.
• Ability to communicate technical concepts to non-technical stakeholders.

Responsibilities

• Design and build the data quality check suite: engineer complex DQ checks and reusable frameworks.
• Architect anomaly detection and monitoring: develop statistical and ML-based detection and reusable wrappers.
• Own engineering standards and reference patterns: define best practices and patterns for DQ implementation.
• Operationalize data quality dashboards: build the pipeline behind the Data Quality Index for real-time health views.
• Ensure accuracy and continuous tuning of checks: validate and tune checks to maximize true detections.
• Proactive detection & monitoring: implement alerting and observability for proactive issue detection.
• Data governance alignment: implement technical controls aligned with data governance policies.

Skills

Problem Solving

Stakeholder Communication

Technical Solution Leadership

Analytical Thinking

Attention to Detail

Education

Bachelor's Degree in CS/CE/IS/Statistics

Tools

SQL

Python

Snowflake

DBT

CI/CD

Looker/Tableau/Power BI

Job description

Globe Telecom in the Philippines seeks a Data Quality Lead Expert to own the design, engineering, and continuous improvement of the Data Quality Framework. You will personally engineer complex checks and define patterns used across the data platform.

You will lead through technical excellence, build dashboards, monitor data health, and align data quality with governance, compliance, and business KPIs, while remaining an individual contributor.