Key Responsibilities (Roles & Responsibilities)

Define and evolve the enterprise data architecture roadmap aligned to business goals and digital transformation programs.
Own architecture standards for data platforms (lakehouse/warehouse), data integration, and data products including reference architectures, patterns, and reusable templates.
Design end-to-end cloud data architectures across ADLS Gen2, Azure Synapse/Fabric Warehouse, Databricks/Spark, and streaming/real-time components as required.
Establish and govern data modeling standards (conceptual/logical/physical), dimensional models (star/snowflake), semantic layer design, and performance-optimized data layers.
Architect scalable ETL/ELT and orchestration frameworks using Azure Data Factory/Synapse Pipelines/Fabric Data Factory/Databricks with CI/CD, parameterization, and observability.
Implement data governance and lineage and define metadata standards and stewardship workflows.
Define data quality strategy: profiling, rules, controls, monitoring dashboards, and issue remediation process with measurable SLAs.
Architect master data and reference data management patterns (canonical models, mapping, hierarchy management) and integration with source systems.
Design and enforce security architecture: RBAC/ABAC patterns, data classification, encryption, key management, PII controls, and privacy-by-design.
Drive platform reliability and cost efficiency: workload sizing, performance tuning, capacity planning, and FinOps-oriented optimizations.
Partner with SI Partners to ensure data architecture supports high-performing Power BI/DWH semantic models, self-service analytics, and executive reporting.
Involve in architecture reviews with internal teams and SI partners; mentor engineers/analysts and drive adoption of best practices.
Engage with senior stakeholders (business, product, technology, risk/compliance) to translate requirements into architectural decisions and communicate risks/trade-offs.
Stay current on emerging capabilities in Microsoft Fabric, Synapse, Databricks Lakehouse, and AI-assisted analytics (e.g., Copilot/agentic patterns) and drive modernization initiatives.

CXO & Stakeholder Engagement

Build and maintain strong relationships with key stakeholders to align analytics strategy with business priorities.
Act as a trusted advisor, translating complex data insights into actionable business recommendations.
Ensure stakeholder buy-in for enterprise data initiatives and foster collaboration across functions

Innovation & Emerging Technology

Stay ahead of emerging trends in data, BI, and GenAI, particularly in Microsoft Fabric, Databricks Lakehouse, CoPilot for BI, and Agentic AI architectures.
Champion AI-augmented BI, predictive reporting, and conversational analytics to enhance insight discovery.
Drive continuous modernization through internal hackathons, accelerator programs, and cross-functional innovation initiatives.

Why This Role Matters

The AVP – Data Analytics role is pivotal to building trusted, governed, and scalable enterprise data foundations that accelerate digital transformation, enable real-time and self-service insights, and prepare the organization for GenAI and AI/ML ready data products.

Senior Assistant Vice President