Principal Data Architect

About the role

Define and lead enterprise data architecture aligned with business objectives and digital transformation roadmaps.
Establish enterprise data strategy and operating models supporting analytics, AI/ML, and data monetization initiatives.
Design scalable architectures encompassing data warehouses, data lakes, lakehouses, streaming platforms, and cloud-native ecosystems.
Ensure architecture decisions support long-term business growth, agility, and technology evolution.
Define and enforce architecture standards, frameworks, design principles, and reference architectures.
Conduct architecture reviews and ensure Quality of Architecture (QOA) compliance across programs.
Serve as a trusted advisor to customers and stakeholders, ensuring scalable, secure, compliant, high-performance, and future-ready data ecosystems.

Responsibilities

• Provide strategic leadership across the entire data lifecycle from ingestion and integration to analytics, AI enablement, and data consumption spanning cloud, hybrid, and modern data platforms.
• Lead multi-disciplinary architecture and engineering teams.
• Drive architecture governance processes and resolve technical escalations.
• Identify and mitigate technical, operational, and data-related risks.
• Lead architecture design for modern cloud and hybrid data platforms.
• Own enterprise data governance frameworks, standards, policies, and controls.
• Drive adoption of metadata management, data cataloging, lineage, and data quality practices.
• Ensure compliance with industry regulations, privacy requirements, and organizational security standards.
• Act as a senior escalation point for governance and compliance-related issues.
• Lead architecture solutioning for strategic pursuits, RFPs, and large transformation engagements.
• Assess technical feasibility, estimate effort, identify risks, and define solution approaches.
• Support business development teams with architecture presentations, customer discussions, and proposal preparation.
• Provide thought leadership and advisory services around enterprise data management and transformation.
• Influence customer technology roadmaps and architecture decisions.
• Develop reusable accelerators, frameworks, templates, and architectural assets.
• Drive adoption of emerging technologies, modern architecture patterns, and AI-ready data platforms.
• Conduct architecture reviews, coaching sessions, and capability-development activities.
• Drive best practices in data engineering, architecture, governance, and platform design.
• Foster a culture of architectural excellence and innovation.

Requirements

• At least 10 years’ experience in enterprise data architecture and large-scale data transformation programs.
• Proven expertise designing cloud-native and hybrid data platforms.
• Strong experience in architecture governance and enterprise-scale solution design.
• Demonstrated success in customer engagement, consulting, solutioning, and presales activities.
• Experience leading multi-disciplinary architecture and engineering teams.
• Strong understanding of data governance, security, compliance, and risk management.

Qualifications

• Master's degree in Computer Science, Information Systems, Engineering, or related field.
• Professional certifications such as Certified Data Management Professional (CDMP), Certified Data Governance Professional (CDGP), or similar.
• Experience with major data platforms like AWS, Azure, GCP, Databricks, Snowflake, etc.
• Knowledge of data modeling, data warehousing, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data lakes, data 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