Platform and Reliability Engineer

Moved analytics discovery toward self-service by connecting a multi-LLM graph runtime with knowledge retrieval, governed Trino execution, answer reasoning, chart generation, prompt tracing, and a richer Open WebUI experience. The natural-language analytics path reduced query time by about 40% for supported workflows.

Improved developer experience, reduced CI/CD onboarding time by about 40%, and increased CI/CD adoption several-fold by replacing bespoke Jenkins pipelines with a small project-level YAML file, reusable templates, automated quality gates, and Jira-triggered delivery flows.

Reduced infrastructure cost by about 30% while improving workload isolation, resource management, deployment repeatability, and scalability for data workloads.

Made access policy behavior more expressive and supportable by marrying tag-based governance with row-level security, masking, extensible attributes, query-engine integration, and audit/error visibility.

• Built governed self-service data platform capabilities around Kyuubi customizations, Trino query access, DataHub metadata, dbt transformations, Metabase BI, RBAC, and secrets management.
• Migrated 50+ Spark and data workloads to Red Hat OCP using Spark Operator, shared CI/CD, Docker/Helm packaging, and Kubernetes runtime conventions, reducing infrastructure cost by about 30%.
• Extended Apache Ranger-based access governance with an external attribute store, DataHub tag-driven policies, row-level security, masking, Trino integration, clearer audit/error paths, and local/containerized runtime support.

• Built automations that saved 500+ manual hours per year by removing repetitive workflow steps.
• Worked in both mainframe and big data ecosystems and contributed to migration from mainframe workloads to Spark-based processing.
• Worked as a developer for insurance and telecom clients across enterprise systems and data workflows.

• Worked as a bridge between data science and big data platform teams by turning analytical work into reusable products and repeatable pipelines.
• Built customer segmentation, data marts, reporting platforms, and retail optimization analytics for large datasets, including category/adjacency work associated with up to 20% sales-growth impact.
• Created reusable retail analytics workflows across customer priority assortment, cross-shopping behavior, direct-mail promotion planning, category uplift, and seasonality analysis.