Senior AVP Enterprise Digital - Lead Data Management

This 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-ready data products.

 

Responsibilities

• 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.

Qualifications

•  

  • 12–15 years of experience across data architecture, data engineering, BI/analytics, and data management leadership.
  • Hands-on experience designing and implementing enterprise-scale data platforms on Azure/Microsoft Fabric.
  • Experience working with corporate function domains such as Finance, HR, and Technology data sets and controls.
  • Strong stakeholder management and ability to influence CXO-level decision making with clear architectural narratives.
  • Bachelor’s degree in Engineering/Computer Science/IT (or equivalent).

  Required Technical Skills

  • Microsoft data platform: Azure Synapse Analytics, ADLS Gen2, Microsoft Fabric (Lakehouse, Warehouse, Data Factory), and Power BI semantic modeling.
  • Data engineering: Databricks, Spark/PySpark, SQL, Python; strong understanding of batch and streaming patterns.
  • Integration & orchestration: Azure Data Factory, Synapse Pipelines, event-driven patterns (e.g., Event Hubs/Service Bus) where applicable.
  • Data modeling: dimensional modeling, semantic layer design, KPI frameworks, and query/performance optimization.
  • Governance: Microsoft Purview, lineage/metadata management, data cataloging, stewardship operating model.
  • Security: Azure RBAC, managed identities, Key Vault, network isolation patterns, and privacy controls.
  • DevOps: CI/CD for data (Azure DevOps/Git), IaC concepts, testing automation, and monitoring/alerting.
  • Architecture methods: reference architecture creation, design documentation, NFRs, and trade-off analysis.

  Preferred Certifications

  • Microsoft Certified: Fabric Data Engineer Associate or Power BI Data Analyst Associate.
  • Databricks Certified Data Engineer / GenAI Engineer Associate.
  • SAFe Agile / PMP / Scrum certifications (CSM/PSM) preferred.