- Strategy, Roadmap & Service Ownership
o Align the analytics roadmap with enterprise Data & Analytics strategy, business outcomes, and service line priorities, ensuring fit-for-purpose analytics products prioritized by measurable value and ROI.
o Define analytics service offerings (self-service reporting, curated datasets and semantic models, reusable analytics patterns, and tiered service levels).
- Insight Delivery, Quality & Governance
o Establish standards for analytics-ready (gold-layer) datasets, semantic models, and metric definitions to ensure consistent, trusted, and certified reporting.
o Sponsor data quality and observability for analytics outputs, including SLAs for data freshness and availability against consumer expectations.
o Ensure governance-by-design across analytics: standardized access, classification/metadata, end-to-end lineage, retention controls, and certified datasets.
o Partner with Data Governance, Privacy, and Data Owners/Stewards to ensure analytics outputs are accurate, compliant, and responsibly and ethically used.
- Analytics Engineering & Delivery Leadership
o Mature analytics engineering standards, reference patterns, and semantic models across the Medallion (Bronze/Silver/Gold) architecture, leveraging dbt for transformation and Power BI for delivery.
o Drive analytics automation and productivity: CI/CD for analytics assets, semantic-layer reuse, and AI-ready data preparation (including Snowflake Cortex AI enablement).
o Provide executive-level stakeholder management for analytics delivery commitments, intake and prioritization, and escalations.
o Build and lead a high-performing team of analytics engineers.
o Define operating model, roles, sourcing strategy (including global delivery centers), and technical and analytics career paths.
o Set measurable goals for adoption, data quality, delivery velocity, cost, and user satisfaction.