Head of Enterprise Data Analytics

5 days ago

Pasig, National Capital Region, Philippines Converge ICT Solutions Inc. Full time $80,000 - $120,000 per year

Role Summary:

Leads strategy, execution, and governance of enterprise data analytics initiatives

Oversees analytics, BI, and data science to support data-informed decisions, innovation, and operational excellence

Partners with business and IT to scale analytics platforms and insights across the organization

Experience:

  • 10+ years in data analytics roles
  • At least 5 years in senior or leadership-level analytics roles
  • Experience in enterprise environments and digital transformation programs

Certifications (Preferred):

  • Google Data Engineer, AWS Certified Data Analytics, Azure Data Scientist Associate
  • CDMP, PMP, or similar data/analytics certifications

Tools & Platforms:

  • Power BI, Tableau, Looker, Qlik
  • Snowflake, BigQuery, Databricks
  • Python, R, dbt, Airflow
  • Familiar with CI/CD and DevOps for analytics pipelines

Skills & Competencies

Strategic Leadership:

  • Develop and align analytics strategy with corporate goals
  • Drive enterprise-wide analytics maturity and value realization
  • Data Storytelling:
  • Translate complex analytics into actionable insights
  • Engagement with C-level stakeholders

Technical Acumen:

  • Strong background in data engineering, modeling, and advanced analytics
  • Familiarity with AI/ML use cases and platforms

Stakeholder Engagement:

  • Proven experience influencing across business, IT, and executive levels

Compliance and Governance:

  • Knowledge of data privacy, regulatory, and compliance standards
  • Ensures secure and ethical data usage across the enterprise

Innovation Mindset:

  • Constantly explores emerging analytics tools and trends
  • Able to lead experiments and innovation pilots

Key Responsibilities

Enterprise Analytics Strategy:

  • Set the vision, roadmap, and priorities for analytics across the company
  • Align data and analytics initiatives with strategic transformation goals

Data Platform Ownership:

  • Build and optimize cloud-native and hybrid analytics infrastructure
  • Ensure scalable and secure data lake/warehouse environments

Advanced Analytics & AI Enablement:

  • Lead the design and delivery of predictive, prescriptive, and AI models
  • Collaborate with data scientists and business units for impactful use cases

BI & Reporting Governance:

  • Standardize enterprise dashboards, KPIs, and reporting tools
  • Promote self-service analytics culture with proper guardrails

Team Leadership & Development:

  • Manage and grow a team of analysts, engineers, data scientists, and BI developers
  • Champion upskilling and modern data practices

Stakeholder Alignment:

  • Gather requirements, prioritize initiatives, and deliver insights to C-level executives
  • Translate business questions into data use cases

Data Governance & Quality:

  • Partner with governance and engineering to maintain metadata, lineage, and quality
  • Enforce consistent data definitions and access policies

Performance Measurement:

  • Define KPIs for analytics programs
  • Monitor business impact and continuously improve

Innovation & Emerging Tech:

  • Evaluate new technologies (e.g., GenAI, AutoML, graph analytics)
  • Lead proofs of concept and strategic innovation pilots

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