Head of Data Architecture and Delivery

Emapta Global; Manila; Hybrid; PHP 1,000,000 - 1,800,000; Full time

Benefits offered by this job

Hybrid work arrangement

HMO coverage with dependent

Office in Makati (PNB Building)

Annual leave credits

Salary advance program

Upskilling via Emapta Academy

Gym access

Employee referral incentives

Job summary

Emapta Global is seeking a Head of Data Architecture and Delivery to steer enterprise data architecture, oversee migrations, and establish standards across international operations. You will mentor engineers and drive data governance, security, and AI-ready data practices across a hybrid Makati-based setup.

You will lead data platforms enabling analytics and ML, manage complex data migrations, and collaborate with executive stakeholders to align data strategy with business goals.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field.
• More than 8 years of experience in data engineering or data architecture, with over 3 years in a data team leadership role.
• Proven experience designing and implementing enterprise data architectures across operational and analytical workloads.
• Hands-on experience in data governance frameworks (cataloging, lineage, contracts, master data).
• Experience in creating enterprise data platforms that support analytics and ML in regulated environments.

Responsibilities

• Direct the design and implementation of enterprise data architecture and standards for reporting, analytics, and AI.
• Translate strategy into practical designs, standards, and implementation plans.
• Lead data architecture and engineering teams to ensure pipelines and data products meet quality and security standards.
• Apply AI-assisted tools to improve productivity and ensure AI outputs are validated before production.
• Design and enforce data governance, security, and privacy controls across platforms.
• Build semantic layers and metric definitions for consistent cross-domain reporting.
• Direct data pipelines, migrations, and centralization efforts across systems.
• Design ML pipelines and retrieval-ready unstructured data with governance and lineage.
• Mentor and develop data engineers and analysts, manage recruitment and budget.
• Collaborate with software delivery to set API contracts and secure data access patterns.
• Present technical findings to leadership and elevate critical issues.

Skills

3NF

Data Vault

SQL

Python

ETL/ELT

CDC

Data Governance

Data Security

AI-ready data architecture

Architectural trade-offs

Education

Bachelor's degree in Computer Science/IT/Data Engineering

Job description

Lead the Minds Architecting the Future of Global Business Intelligence

Guide exceptional technology professionals toward a smarter, more connected global enterprise. As Head of Data Architecture and Delivery, you'll mentor engineers, oversee complex data migrations, and establish architecture standards across international operations. Pursue a long-term career with Emapta, where your leadership improves business intelligence, strengths organizational resilience, and supports meaningful professional growth within a Top 1% talent community.

Job Overview

• Employment Type: Full-time
• Shift: Flexible Shift | Weekends Off
• Work Setup: Hybrid | PNB Building, Makati

Exciting Perks Await!

• Competitive Salary Package
• Hybrid work arrangement
• HMO coverage with free dependent upon regularization
• Prime office location in Makati (easy access to MRT stations, restaurants, and banks)
• Fixed weekends off
• Salary Advance Program through our banking partner (Eligibility and approval subject to bank assessment. Available to account holders with a minimum of 6 months of company tenure.)
• Unlimited upskilling through Emapta Academy courses (Want to know more? Visit: https://emapta.com/training-calendar/)
• Free 24/7 access to our office gyms (Ortigas and Makati) with a free physical fitness trainer!
• Exclusive Emapta Lifestyle perks (hotel and restaurant discounts, and more!)
• Unlimited opportunities for employee referral incentives across the organization
• Standard government and Emapta benefits
• A total of 20 annual leave credits to use at your discretion (including 5 credits convertible to cash)
• Fun engagement activities for employees
• Mentorship and exposure to global leaders and teams
• Career growth opportunities
• Diverse and supportive work environment

The Qualifications We Seek

Educational Background

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

Professional Experience

• More than 8 years of experience in data engineering or data architecture, with over 3 years in a data team leadership role.
• Proven experience in designing and implementing enterprise data architectures across operational and analytical workloads.
• Extensive experience in managing data migration and consolidation programs, including complex, inconsistent, and manually maintained data sources.
• Hands-on experience in implementing data governance frameworks, including data cataloging, lineage, data contracts, and master and reference data management.
• Experience in developing enterprise data platforms that support analytics and machine learning within regulated or certified environments.

Technical Knowledge and Skills

• Advanced knowledge of data architecture and modeling methodologies, including Third Normal Form (3NF), dimensional modeling, and Data Vault.
• Strong understanding of modern data platform architectures, including data warehouses, lakehouses, medallion architectures, batch processing, streaming, and change data capture (CDC).
• Advanced proficiency in SQL, working knowledge of Python, and practical experience with production-scale ETL and ELT pipelines.
• Comprehensive knowledge of data governance, quality, and security practices, including role-based access control, row-level security, data masking, and encryption.
• Strong understanding of AI-ready data architecture, including retrieval-ready unstructured data, feature pipelines, and end-to-end data lineage.
• Sound judgment in evaluating architectural trade-offs and selecting appropriate solutions for enterprise requirements.

Leadership and Communication Skills

• Proven leadership and coaching skills, with experience in managing, mentoring, and developing data engineers and analysts.
• Excellent communication and stakeholder management skills, with the ability to explain complex technical concepts to business data owners and executive stakeholders.

Preferred Qualifications

• Cloud data platform certification in AWS, Azure, Databricks, or an equivalent technology.
• Experience with human capital management (HCM), human resource information systems (HRIS), or workforce management data.
• Experience in establishing semantic layers or metric stores from scratch.

Your Daily Tasks

Enterprise Data Architecture and Delivery

• Direct the design and implementation of enterprise data architecture, including data models, platform structures, and technical standards that establish a trusted foundation for reporting, analytics, and artificial intelligence (AI).
• Translate the architectural strategy established by the Director into practical designs, technical standards, and implementation plans.
• Lead the data architecture and engineering team to ensure all pipelines, schemas, and data products comply with established quality, governance, and security standards.

AI-Enabled Data Productivity

• Apply AI-assisted tools to improve productivity and accuracy across data engineering activities and measure their impact on delivery performance.
• Establish accountability for human validation of AI-generated outputs before production deployment, including schema changes, transformation logic, data quality rules, and access control designs.
• Prevent the exposure of proprietary, client, and workforce data to unapproved AI models through data profiling, documentation, or code generation tools.

Data Governance, Quality, and Security

• Implement the data governance framework established by the Director and Chief Information and Digital Officer (CIDO), including data cataloging, lineage, quality, contracts, and master and reference data management.
• Design domain-specific security controls, including role-based access, row-level security, data masking, and encryption.
• Incorporate privacy and regulatory compliance requirements into platform architecture, including GDPR, the Philippine Data Privacy Act, Australian Privacy Principles (APPs), and HIPAA, where applicable.
• Review and approve data dictionaries and source-to-target mappings in collaboration with data owners and stewards.
• Assess and report the governance readiness of tier‑one data domains, and elevate unresolved data ownership or quality concerns.
• Direct the data architecture and governance of the centralized API layer that controls application and AI access to enterprise data.
• Collaborate with the Head of Software Delivery to establish API contracts, integration standards, and secure data access patterns.

Data Architecture and Modeling

• Direct the design of enterprise data architectures and models across operational (OLTP) and analytical (OLAP) workloads, from conceptual to physical implementation.
• Establish and maintain data modeling standards, including Third Normal Form (3NF), dimensional modeling, and Data Vault methodologies.
• Evaluate data warehouse, lakehouse, medallion, batch processing, streaming, and change data capture (CDC) architectures.
• Document architectural trade-offs and present recommendations on major platform and integration decisions to the Director.
• Develop and maintain semantic layers and standardized metric definitions to ensure consistent reporting across business domains.

Data Pipelines, Centralization, and Migration

• Direct the architecture and implementation of data pipelines that consolidate information from operational databases, flat files, third-party applications, and SaaS platforms.
• Oversee enterprise data migration and consolidation initiatives, and report progress, risks, and issues to the Director.
• Establish standards for schema mapping, data deduplication, and reconciliation, including processes for inconsistent and manually maintained data sources.
• Facilitate technical design reviews with data engineering teams and develop prototypes to validate proposed architectural solutions.

AI and Analytics Enablement

• Design data models and access frameworks that support business intelligence (BI) and self-service analytics.
• Establish architecture for machine learning pipelines and retrieval-ready unstructured data, including vectorization, chunking, and metadata standards for retrieval-augmented generation (RAG).
• Ensure data accessed by AI systems retains its classification, security permissions, and lineage through to the point of use.
• Establish controls that enable traceability to original data sources and prevent unauthorized access to restricted information.
• Design audit-ready logs and lineage records that capture AI-assisted decisions, input data, model versions, and human reviewers.
• Define and monitor data quality thresholds for AI and analytics deployments, and prevent the release of solutions that fail to meet established standards.
• Direct remediation of data quality issues at their source rather than rely on downstream corrections.

Team Leadership and Development

• Direct, coach, and develop the data architecture and engineering team through clear objectives, performance management, and professional development.
• Mentor data engineers and analysts on data modeling, architectural design, and technical decision-making.
• Address behavioral and performance concerns that affect team effectiveness and delivery standards.
• Manage recruitment and workforce planning for the data function within approved staffing and budget parameters.

Stakeholder Collaboration and Executive Reporting

• Collaborate with software engineering, analytics, information security, and business data owners to ensure effective architectural implementation.
• Conduct vendor assessments, technology evaluations, and proofs of concept to support informed platform decisions.
• Present technical findings and recommendations to the Director for review and approval.
• Report architectural progress, delivery risks, and key decisions to the Director, and elevate matters that require executive intervention.

Other Responsibilities

• Perform additional administrative or operational duties as assigned by authorized company representatives through written or verbal instructions.

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