• Review and assess GMCB's existing Data Governance Charter; deliver charter improvement recommendations covering decision rights, policies, stewardship models, and governance workflows (Deliverable B1) • Conduct a Metadata and Stewardship Standards Assessment covering data dictionaries, metadata practices, stewardship assignments, and data collection standards (Deliverable B2) • Develop the Updated Governance Standards Package including revised charter, RACI matrix, refined stewardship roles, metadata standards, and Data Governance Playbook v1.0 (Deliverable B3) • Author the comprehensive Data Governance Playbook covering governance framework, data asset profiles (VHCURES, VUHDDS, ASSR), data quality standards, and stewardship procedures • Design and deploy the Governance Dashboard Suite in Power BI: Governance Activity, Compliance, Data Quality, and Stewardship Performance dashboards (Deliverable B4) • Develop and deliver Governance Training & Enablement Materials for GMCB Data Stewards and leadership (Deliverable B5) • Design integration patterns between Azure Databricks, ADO, and Power BI to support automated data quality monitoring and governance compliance tracking • Establish data quality standards, lineage tracking, and metadata governance aligned with HIPAA requirements for regulated health datasets • Define governance workflows, approval triggers, and policy enforcement mechanisms using Power Automate and ADO pipelines • Collaborate with the DevOps Engineer and Agile Coach to embed governance checkpoints into sprint workflows and CI/CD pipelines

• Build and maintain production quality data pipelines between operational systems and BigQuery (ingress and egress). • Implement data quality and freshness checks and monitoring processes to ensure data accuracy and consistency. • Maintain and contribute to our ingestion framework that leverages various purpose-built data load tool (dlt) connectors. • Create and maintain comprehensive documentation for data engineering processes, systems, and workflows • Maintain observability and monitoring of our internal data pipelines. • Troubleshoot and resolve data pipeline issues to ensure downstream data availability. • Contribute to our dbt systems by making sure the source and staging layers align with our standards, are efficient, cost-effective, and highly available. • Participate in the investigation and implementation of event-driven data movement and transformation processes. • Participate in the investigation and implementation of analytic data storage/table formats (e.g. Apache Iceberg)

Role Description As a Data Engineer, you will help us build our information system, which is used by our staff globally. The RISE mission is to accelerate the internet for the Philippines—we do this by focusing on the overall customer experience, providing excellent internet services and creating a positive impact on our partners and industry. - Analyze and develop solutions to information needs in our business - Design, develop, deploy, and test new information and data processing applications in accordance to our quality standards - Perform preventive maintenance, identify and execute improvements, and refactor existing code base, including our legacy applications - Monitor, respond, and resolve incidents in production - Develop and maintain the infrastructure that hosts our applications in production - Support our internal staff and stakeholders’ inquiries and issues with the applications in use - Investigate and create proofs of concepts, such as in using external services, APIs, programming libraries, and data source systems - Contribute in the development of user guides and knowledge base of applications in use Qualifications - Bachelor’s degree in Information Technology or Computer Science - 3+ years of experience in software engineering, using any of the following programming languages: Ruby, Javascript, Python, and PHP - Proficiency in developing scripts and applications for data ETL and reporting purposes - Proficiency in standard software engineering practices (i.e. source code management, continuous integration, automated tests, pair programming) - 2+ years experience in end-to-end IT management - Proficiency and hands-on experience with implementing, configuring, and testing IT solutions - Experience in using cloud services and APIs, preferably with Amazon Web Services (AWS) - Administration and shell usage of Linux-based systems (CentOS, Ubuntu) - Highly customer-focused and able to provide a positive experience in conflict resolution - Excellent communication skills and able to effectively convey messages or know-how to non-technical customers - Highly dependable and responsive especially in urgent or time-sensitive situations - Able to maintain high level of integrity and confidentiality Benefits - An environment of a sports team that is there to coach each other while being performant. - A data and software culture that strives to build high quality IT systems. - An organization of autonomous teams, exploring and trying out solutions in a safe environment. - A place for you to learn, practice, develop yourself, and contribute to something meaningful. - A front seat at a fast growing, global company with a lot of opportunities in software, IT, and technology with exposure in telecommunications and web. - Flexibility and a wide array of health and well-being incentives to keep you balanced. - An opportunity to work with some of the best and smartest people around.

• Architect & Build Data Pipelines: Design, construct, install, test, and maintain highly scalable data management systems and ETL/ELT pipelines. • Integrate Diverse Data Sources: Develop processes to ingest and integrate high-volume, high-velocity data from SCADA systems, historians, DCS, PLC, and IoT sensors. • Cloud Data Platform Development: Implement and manage data solutions on Microsoft Azure, leveraging services like Azure IoT Hub. • Data Modelling & Warehousing: Design and implement data models optimized for time-series data from industrial assets. • Enable Advanced AI: Build the data infrastructure to support AI/ML models for predictive maintenance and anomaly detection. • Champion Master Data Management (MDM): Create a single source of truth for critical data domains. • Ensure Data Quality & Governance: Implement data quality checks and monitoring to ensure accuracy and consistency. • Embrace Industry Standards: Implement industry-specific standards for interoperability across sectors. • Collaborate & Innovate: Work with cross-functional teams to understand data needs and deliver effective solutions. • Automate & Optimize: Identify automation opportunities to improve data delivery and scalability. • Security First: Maintain security best practices to protect sensitive data assets.