Senior Principal Data Architect

Lead enterprise-scale data architecture, governance, and delivery oversight across cloud and AI-enabled ecosystems, driving modern data platforms, MDM excellence, and business-aligned outcomes.

Key Responsibilities

• Own end-to-end Data Architecture strategy across enterprise platforms (Cloud, On-prem, Hybrid).
• Drive Delivery Governance ensuring quality, timelines, financials, and stakeholder alignment.
• Establish and operationalize Data Governance frameworks (data quality, lineage, catalog, compliance).
• Lead and enhance Informatica MDM (multi-domain) implementations, upgrades, and optimization.
• Architect Cloud Data Platforms (Azure/GCP/AWS) leveraging modern data stack (Data Lakehouse, ETL/ELT, streaming).
• Enable AI/GenAI adoption by designing data foundations for ML, analytics, and intelligent automation.
• Partner with business and IT leadership to translate data strategy into execution roadmaps.
• Define and enforce architecture standards, best practices, and reusable accelerators.
• Mentor teams and influence large-scale data transformation programs.

Must-Have Skills & Experience

• 15+ years in Data Engineering / Data Architecture / Data Platforms

Strong expertise in

• Data Governance tools & framework implementation
• Proven track record in Delivery Governance & large program leadership
• Experience in AI/ML data readiness, GenAI ecosystem exposure

Strong hands-on with

• ETL/ELT tools (ADF, Informatica, Databricks)
• Data Lakes / Lakehouse architectures
• Domain experience in BFSI / Insurance preferred
• Executive stakeholder management (CXO-level interactions)
• Strong ownership of P&L, delivery excellence, and risk management
• Ability to drive innovation, accelerators, and reusable frameworks
• High focus on quality, governance, and scalable design

Nice to Have

• Experience in MDM modernization / migration programs
• Exposure to data privacy regulations (GDPR, etc.)
• Certification in Cloud / Data Architecture frameworks

Outcome Expectation (Success Metrics)

• Robust, scalable enterprise data architecture in place
• Improved data quality, governance maturity, and MDM adoption
• Successful delivery of complex data programs with high stakeholder satisfaction
• Increased AI/analytics enablement through strong data functions

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