Senior AVP, Enterprise Digital – Lead Data Management
Noida, Uttar Pradesh, India
Full Time
5 hours ago
No Sponsorship
Key skills
AzureCloudETLPySparkPythonSparkSQLVaultAIAgenticELTData EngineeringAnalyticsBIPower BISnowflakeDatabricksAzure DevOpsService BusGitPerformance OptimizationCI/CDLeadershipStakeholder ManagementDecision Making
About this role
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.