Head of Enterprise Data Analytics

Role Summary:Leads strategy, execution, and governance of enterprise data analytics initiativesOversees analytics, BI, and data science to support data-informed decisions, innovation, and operational excellencePartners with business and IT to scale analytics platforms and insights across the organizationExperience:10+ years in data analytics rolesAt least 5 years in senior or leadership-level analytics rolesExperience in enterprise environments and digital transformation programsCertifications (Preferred):Google Data Engineer, AWS Certified Data Analytics, Azure Data Scientist Associate   CDMP, PMP, or similar data/analytics certificationsTools & Platforms:Power BI, Tableau, Looker, QlikSnowflake, BigQuery, DatabricksPython, R, dbt, AirflowFamiliar with CI/CD and DevOps for analytics pipelinesSkills & CompetenciesStrategic Leadership:Develop and align analytics strategy with corporate goalsDrive enterprise-wide analytics maturity and value realizationData Storytelling:Translate complex analytics into actionable insightsEngagement with C-level stakeholders Technical Acumen:Strong background in data engineering, modeling, and advanced analyticsFamiliarity with AI/ML use cases and platforms Stakeholder Engagement:Proven experience influencing across business, IT, and executive levelsCompliance and Governance:Knowledge of data privacy, regulatory, and compliance standardsEnsures secure and ethical data usage across the enterpriseInnovation Mindset:Constantly explores emerging analytics tools and trendsAble to lead experiments and innovation pilotsKey ResponsibilitiesEnterprise Analytics Strategy:Set the vision, roadmap, and priorities for analytics across the companyAlign data and analytics initiatives with strategic transformation goalsData Platform Ownership:Build and optimize cloud-native and hybrid analytics infrastructureEnsure scalable and secure data lake/warehouse environmentsAdvanced Analytics & AI Enablement:Lead the design and delivery of predictive, prescriptive, and AI modelsCollaborate with data scientists and business units for impactful use casesBI & Reporting Governance:Standardize enterprise dashboards, KPIs, and reporting toolsPromote self-service analytics culture with proper guardrailsTeam Leadership & Development:Manage and grow a team of analysts, engineers, data scientists, and BI developersChampion upskilling and modern data practicesStakeholder Alignment:Gather requirements, prioritize initiatives, and deliver insights to C-level executivesTranslate business questions into data use casesData Governance & Quality:Partner with governance and engineering to maintain metadata, lineage, and qualityEnforce consistent data definitions and access policiesPerformance Measurement:Define KPIs for analytics programsMonitor business impact and continuously improveInnovation & Emerging Tech:Evaluate new technologies (e.g., GenAI, AutoML, graph analytics)Lead proofs of concept and strategic innovation pilots