GCP + Qlik Data-Ingestion Automation
Owned product for an enterprise data-ingestion automation initiative at Mahindra & Mahindra, as AI Product Manager.
Visit Mahindra & MahindraThe problem
Manual, error-prone data ingestion into Qlik was slowing down internal reporting workflows across the org, and needed a structured, automated pipeline that non-technical stakeholders could trust.
What I owned
- Defined product requirements and roadmap for the automation initiative, translating between technical GCP/Qlik implementation details and business stakeholders.
- Ran stakeholder alignment across teams to prioritize which ingestion workflows to automate first.
- Sat alongside two related agentic products - GenieBot, an HR self-service agent, and CaraBot, a vendor-automation agent - as part of the same enterprise AI push, working as a developer on those systems.
Key decisions
- Product-led rollout inside a non-tech-native org - prioritized stakeholder trust and change management alongside technical delivery, since the ingestion pipeline needed adoption from teams unfamiliar with GenAI-driven automation.
Outcome
Time-saved, error-rate, and adoption metrics for the ingestion pipeline will be added here - get in touch if you'd like the details directly.