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A Data Strategy Lead with robust expertise across:
- Observability ecosystems and enterprise systems
- AI-driven automation and self-healing platforms

Role and Responsibilities
- Lead the design of an enterprise observability data layer (data lake / data hub) for unified telemetry:
- Define and implement a scalable common data layer (data lake / data hub) for observability.
- Design modern data architecture including:
- Real-time analytics layer (hot data)
- Historical and ML data layer (cold data)
- Establish data models, schemas, and standards to unify telemetry across systems.
- Enable structured, semi-structured, and streaming data integration.
- Implement data governance, quality, lineage, and security frameworks.
- Enable an AI-ready data foundation for anomaly detection, RCA, and agentic workflows.
- Design data architecture supporting real-time decision-making and autonomous remediation.




- Define architecture for real-time and batch data pipelines, including streaming ingestion, processing, and storage.
- Define data models and schema standards for ERP, applications, and infrastructure telemetry.
- Collaborate with platform teams to ensure monitoring, tracing, and optimization of data pipelines.
- Integrate with observability tools and ERP systems such as S/4HANA, AppDynamics, Dynatrace, Signavio, and SAP BTP Integration Suite.
- Enable closed-loop data flows to support self-healing and intelligent automation:
- Design data flows enabling:
- Anomaly detection and alerting
- AI-assisted root cause identification
- Automated remediation workflows
- Support closed-loop observability, where outcomes are fed back into the system as telemetry.
- Enable Human-in-the-Loop (HITL) controls for governed automation.

📌 Data Strategy Lead – Observability (Noida)
🏢 Topcoder
📍 Noida