Architectural & Platform Leadership
• Own the enterprise architecture for the Azure-based data platform, including Databricks, Azure Data Factory, Delta Lake, and Power BI.
• Define and maintain platform architecture standards, reference patterns, and future-state roadmaps aligned to business strategy.
• Ensure the platform enables analytics, reporting, and AI/ML workloads at enterprise scale.
Data-as-a-Product Operating Model
• Establish and govern Data-as-a-Product standards including ownership, SLAs, documentation, metadata, lineage, and quality requirements.
• Partner with Product Owners and domain teams to enable scalable data product delivery.
Team & Vendor Leadership
• Lead and coordinate all onsite and offshore resources supporting the Operational Data Platform, including L1–L3 support, data engineering, analytics, and platform operations teams.
• Act as the single architectural and operational authority for a hybrid delivery model spanning onshore leadership and offshore execution teams.
• Define clear roles, responsibilities, escalation paths, and RACI frameworks across vendors and internal teams.
• Hold managed service providers accountable for SLAs, security standards, architectural compliance, and operational excellence.
Data Operations & Reliability
• Own the Data Ops operating model including incident management, change governance, release coordination, and production support.
• Establish severity-based support coverage and on-call models.
• Lead root cause analysis initiatives and drive continuous platform reliability improvements.
Governance, Security & Compliance
• Define and enforce governance standards for RBAC, data masking, CI/CD, Infrastructure as Code, and audit readiness.
• Ensure SOX and privacy controls are embedded in platform architecture and operations.
• Serve as technical authority during audits by providing architectural artifacts and operational evidence.
Observability & Continuous Improvement
• Define the observability strategy for pipeline health, data quality, platform metrics, cost telemetry, and SLA enforcement.
• Champion Data Reliability Engineering practices and proactive monitoring.