AI Data Engineer (GAA, Philippines: Cebu)
Indexed description
We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results.
Opportunity Overview
Data Platform Engineering
- Design, develop, and maintain scalable data integration and data processing solutions across enterprise platforms.
- Build and optimize ETL/ELT pipelines using modern cloud-based technologies.
- Develop and maintain data models, datasets, and supporting architecture for analytics, automation, and operational reporting.
- Ensure data quality, reliability, performance, and governance across supported platforms.
- Support platform modernization, migration, and continuous improvement initiatives.
- Administer and support enterprise data platforms including Snowflake, Informatica Cloud, Power BI, and related technologies.
- Monitor platform health, performance, security, and operational usage.
- Troubleshoot complex technical issues and coordinate resolution activities across multiple teams.
- Participate in platform upgrades, maintenance activities, and governance initiatives.
- Develop and maintain operational documentation, standards, and procedures.
- Identify opportunities to eliminate manual processes through automation and technology solutions.
- Design and implement automated workflows, integrations, and operational controls.
- Develop reusable frameworks, scripts, and tools that improve efficiency and reduce operational overhead.
- Promote best practices for automation, operational excellence, and continuous improvement.
- Support AI-driven and intelligent automation initiatives across the organization.
- Develop, administer, and optimize Power BI reporting solutions, semantic models, and dashboards.
- Support enterprise reporting, data visualization, and self-service analytics initiatives.
- Ensure data consistency, governance, and security across reporting environments.
- Work with business and technical stakeholders to translate requirements into analytical solutions.
- Deliver actionable insights through data visualization and performance reporting.
- Evaluate, implement, and support AI-enabled capabilities that improve business operations and user productivity.
- Participate in the design and integration of AI agents, copilots, and intelligent automation solutions.
- Collaborate with architecture, engineering, and business teams to identify high-value AI use cases.
- Stay current on emerging technologies and industry best practices.
- Contribute to the adoption of modern AI and automation capabilities across enterprise platforms.
- Partner with cross-functional teams to deliver technology solutions aligned with business objectives.
- Provide technical guidance and mentorship to team members.
- Participate in planning, prioritization, and execution of strategic initiatives.
- Communicate effectively with both technical and non-technical stakeholders.
- Foster a culture of teamwork, accountability, empathy, and continuous improvement.
- 4+ years of experience in Data Engineering, Analytics Engineering, Data Platform Engineering, Business Intelligence Administration, or related roles.
- Bachelor’s degree in Business, Information Systems, or a related field required
- Hands-on advanced experience with Informatica Intelligent Cloud Services (IICS / CDI-PC).
- Hands-on advanced experience with Snowflake, including SQL development, performance optimization, data modeling, security concepts, and operational monitoring.
- Hands-on experience administering and developing in Power BI, including workspaces, datasets, semantic models, refresh schedules, gateways, security, and reports.
- Problem Solver: Demonstrated ability to independently analyze complex problems, identify root causes, and deliver practical solutions without creating unnecessary operational overhead.
- Ownership: Strong sense of accountability, follow-through, and bias toward execution.
- Teamwork: Collaborative mindset with the ability to work effectively across support, engineering, architecture, security, and business teams.
- Adaptability: Comfortable working through ambiguity, changing priorities, and evolving AI/data platform technologies
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