Head of Enterprise Data Analytics
2 weeks ago
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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