Rohith Reddy Kota

One of the earliest engineers at Rill, an open-source, real-time operational BI platform. Owned US time-zone engineering coverage on a distributed, multi-time-zone team.

Forward deployed & solutions engineering

• Lead end-to-end deployments for 50+ enterprise customers, from scoping and architecture to build, go-live, and handoff, through customer GitOps repos, dedicated clusters, and BYOC installs.
• Ran 150+ proofs of concept with Sales and GTM, covering discovery, solution design, technical demos, and a working deployment.
• Own SSO integration and lifecycle (SAML, OIDC, OAuth2), row-level security, and customer-side S3 and GCS bucket policies, service accounts, and access scoping.
• Migrate customers from legacy systems to Rill, and move data between Snowflake, Redshift, Iceberg, or Delta Lake and ClickHouse or Druid, including reverse ETL, with parity checks before every cutover.
• Build and maintain Helm charts for Druid and ClickHouse, and support customers running Rill in their own cloud (BYOC).

Product management & customer success

• Primary technical contact across enterprise accounts: onboarding, user training, recurring roadmap reviews and feature demos, requirements with technical and executive stakeholders, and escalations.
• Turn requirements from 50+ accounts into roadmap input, and work with Product and Engineering to prioritize and ship customer-driven integrations.
• Architected incremental ingestion for Rill’s ClickHouse driver, the foundation for ClickHouse data modeling in Rill, while preserving idempotency.
• Built internal tooling for the solutions team, including MCP servers, agent skills, and structured-output LLM integrations, cutting repetitive work across engagements.
• Player-coach for 2 engineers. Write and review design docs, and break work into epics, stories, and estimates.

Platform & data infrastructure

• Manage 2+ PB on Kubernetes (GKE) across ClickHouse, Druid, and DuckDB, including 30+ database clusters (17 Druid, 14 ClickHouse), with Helm, Terraform, and custom Go operators.
• Tune ingestion, compaction, and physical design (sort keys, partitions, projections, codecs, TTLs) to cut storage and CPU by ~30–40% and scan TBs of data in under 30 seconds.
• Engineer batch and real-time ingestion at GBs per hour from Kafka, S3, GCS, and lakehouses, with idempotent backfills and failure recovery.
• Debug Kubernetes-level production issues (pod and node failures, cluster instability, operator faults) across multi-tenant GKE clusters.
• Introduced SLOs, burn-rate alerts, runbooks, and postmortems, and built fleet observability dashboards, an AI on-call triage agent, and the usage-billing pipeline.
• Stabilized inherited Kafka, Apache Beam, and Druid pipelines alongside greenfield platform work.

• Designed and built an ML-based ad-moderation service that automatically rejected fraudulent listings, reducing manual moderation work.
• Built stateful Apache Flink streaming over real-time web and mobile clickstream.
• Owned Airflow ETL/ELT jobs, the AWS Redshift data warehouse, and Tableau reporting for business owners and digital marketing teams.
• Designed APIs between the data platform and backend applications with the frontend and backend teams.

• Built streaming and data-intensive analytics in Java and Python over industrial sensor data.
• Ran multi-node Hadoop and Spark clusters and migrated the data stack to AWS EMR.
• Built Go services on MongoDB and gRPC integrations with product engineering teams.

• Migrated ERP data into SAP R/3 using Informatica and the BackOffice Associates Data Stewardship Platform, with MS SQL Server for staging and batch processing.