Mounika Revanuru

When I stepped into this engagement, the data platform was fragmented, reporting was slow, insights were delayed, and teams relied heavily on engineers. I led the transformation by guiding a cross-functional team to build a scalable, cloud-native ecosystem that balances performance and usability. We reimagined Power BI into a self-service analytics layer, putting data directly in the hands of business users and accelerating decision-making.

At the same time, I ensured stability by overseeing production support by introducing monitoring, reducing recurring issues, and improving trust in the system. We also uncovered critical security gaps, which I addressed by strengthening access controls and aligning with enterprise governance standards.

Since the platform was being modernized in phases, I drove interim solutions that kept external users seamlessly and securely connected. Throughout, I kept stakeholders closely aligned with clear communication, risk visibility, and consistent progress updates.

The result was more than a platform upgrade: it was a shift to a scalable, secure, and insight-driven data ecosystem that teams could rely on.

The data platform had strong potential but lacked structure. There was a mix of raw and partially processed data, and much of the business logic was held as tribal knowledge by a few subject-matter experts. I led an effort to bring order and scalability by driving the transition to a medallion architecture, creating clear layers for raw, refined, and curated data.

Working closely with domain experts, we translated their knowledge into curated business views, standardizing definitions and making data consistently usable across teams. These transformations were automated through robust pipelines, enabling continuous and reliable data refresh without manual intervention.

To expand analytical adoption, I led the integration of multiple data sources into Databricks, creating a unified foundation for advanced analytics. In parallel, I initiated a hackathon to showcase Databricks Genie, enabling users to query data using natural language rather than SQL. This gained strong traction and evolved into a full-scale project, which I now lead to make data access more intuitive and democratized.

Overall, the focus has been on transforming scattered data into a structured, trusted, and scalable platform aligned with business needs.