Senior AVP, Enterprise Digital – Lead Data Management

Role Overview

• 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.

Requirements

• 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.

Tech Stack

• Azure
• Cloud
• ETL
• PySpark
• Python
• Spark
• SQL
• Vault

Benefits

• Health insurance
• Retirement plans
• Paid time off
• Flexible work arrangements
• Professional development
• Bonuses
• Stock options
• Equipment allowances
• Wellness programs