Data & Applications Development Lead

VITRO, Inc.; Makati; On-site; PHP 3,000,000 - 6,000,000; Full time

Job summary

VITRO, Inc. in Makati/South Manila region is seeking a senior Data Strategy & Management leader. You will define enterprise data strategy, governance, and architecture, and lead AI-enabled application development and API-driven integration across systems.

The role requires extensive experience in data warehouses, ETL/ELT, MuleSoft, and Microsoft Fabric, with a strong focus on security, compliance, and scalable cloud-native solutions. A dynamic, collaborative environment awaits.

Qualifications

• Bachelor's degree in IT/CS/CE or data-related field.
• 10+ years in IT, data management, engineering or development.
• 5+ years in leadership or management roles.
• Proven enterprise data warehouse, API, and integration leadership.
• Experience with cloud, Agile, DevSecOps, and EA.
• Vendor and project budget management experience.

Responsibilities

• Develop and implement the organization’s data strategy.
• Establish data governance standards and operating models.
• Ensure data accuracy, security, and accessibility.
• Promote a data-driven culture with trusted data and AI insights.
• Lead enterprise data warehouse architecture and ETL/ELT pipelines (Microsoft Fabric).
• Oversee API strategy and secure API delivery (MuleSoft).
• Manage AI-enabled applications and enterprise solutions.
• Define target architecture aligned with cloud strategy and roadmaps.
• Lead cross-functional teams and manage project portfolios.

Skills

Data strategy

Data governance

Leadership

AI & Gen AI

Cloud computing

Agile methodologies

DevSecOps

Vendor management

Solution architecture

Education

Bachelor's degree in Information Technology

Data Science degree

Tools

MuleSoft Anypoint

Microsoft Fabric

CI/CD tooling

Job description

Job Description: Data Strategy and Management

• Develop and implement the organization’s enterprise data strategy aligned with business and technology objectives.

• Establish and maintain data governance standards, policies, and operating models across the data lifecycle.

• Ensure enterprise data is accurate, secure, accessible, and reliable for business use.

• Promote a data-driven culture by improving access to trusted data, analytics, reports, and AI-enabled insights.

Data Warehouse and Engineering

• Lead the architecture, development, and continuous improvement of the enterprise data warehouse using Microsoft Fabric.

• Oversee the development of scalable and automated ETL/ELT pipelines.

• Manage data integration across enterprise systems, cloud platforms, operational systems, and external data sources.

• Establish standards for data modeling, transformation, testing, deployment, documentation, and performance monitoring.

• Drive the modernization of legacy data platforms and manual processes.

API Management and Systems Integration

• Lead the organization’s API strategy, architecture, governance, and delivery using MuleSoft.

• Oversee the design, development, deployment, and management of secure and reusable APIs.

• Promote API-led connectivity and seamless integration across enterprise systems and third‑party services.

• Establish standards for API security, versioning, documentation, monitoring, and lifecycle management.

Application Development and AI

• Lead the planning, design, development, implementation, and support of enterprise applications.

• Oversee the delivery of web, mobile, workflow, automation, integration, and AI-enabled solutions.

• Lead the development and implementation of Agentic AI solutions, intelligent automation, and AI-assisted workflows.

• Identify business opportunities where AI agents and emerging technologies can create measurable business value.

• Establish appropriate controls for responsible AI, including security, data privacy, human oversight, and risk management.

Technology Leadership and Governance

• Define and maintain the target architecture for data platforms, APIs, applications, and AI solutions.

• Ensure alignment with enterprise architecture, cloud strategy, cybersecurity standards, and technology roadmaps.

• Review solution designs and promote scalable, modular, secure, and reusable technology solutions.

• Evaluate emerging technologies based on business value, scalability, security, and total cost of ownership.

Project and Team Management

• Manage the data, integration, application development, and AI project portfolio.

• Lead multidisciplinary teams across data engineering, API development, software engineering, DevOps, QA, AI engineering, and solution architecture.

• Manage project priorities, resources, budgets, timelines, risks, and external technology partners.

• Coach and develop team members while fostering a culture of innovation, accountability, collaboration, and continuous improvement.

Job Qualifications:

• Bachelor’s degree in Information Technology, Computer Science, Computer Engineering, Data Science, Software Engineering, or a related field.

• At least 10 years of progressive experience in information technology, data management, data engineering, systems integration, or application development.

• At least 5 years of experience in a leadership or management role.

• Proven experience in managing enterprise data warehouses, ETL/ELT platforms, APIs, systems integration, and application development teams.

• Experience in delivering enterprise-scale digital transformation, data modernization, or AI initiatives.

• Experience working with cloud-based platforms, Agile methodologies, DevSecOps, and enterprise architecture.

• Experience in managing vendors, technology partners, project budgets, and cross‑functional teams.

• Strong knowledge of Microsoft Fabric.

• Strong understanding of data warehouses, data lakes, lakehouses, and data marts.

• Knowledge and experience in ETL/ELT architecture and development.

• Strong knowledge of data modeling, dimensional modeling, and semantic models.

• Knowledge of data quality, metadata management, data lineage, and master data management.

• Experience with MuleSoft Anypoint Platform.

• Knowledge of API design, API-led connectivity, integration patterns, and API security.

• Knowledge of cloud architecture and cloud-native application development.

• Experience in web and mobile application development.

• Knowledge of microservices and event‑driven architecture.

• Experience with DevSecOps, CI/CD, source code management, and automated testing.

• Knowledge of Artificial Intelligence, Generative AI, Large Language Models (LLMs), and Agentic AI.

• Understanding of Retrieval-Augmented Generation (RAG) and enterprise knowledge systems.

• Knowledge of AI orchestration frameworks, evaluation, monitoring, guardrails, and responsible AI.

• Knowledge of Agile, Scrum, product management, and project portfolio management.