Aiswarya Vijaya Kumar
Data Engineer @ Amazon
About
AI/ML Data Engineer with end-to-end experience building the data infrastructure behind production ML and agentic systems from batch and streaming pipelines to LLM applications, feature stores, and ML platforms across AWS/Snowflake/Spark/Bedrock. Let's connect! I'm always open to discussing AI/ML platforms, agentic systems, or new career opportunities.
United States
San Francisco Bay Area
Computer Software
Enterprise Data Warehouses (EDW), ETL Tools, PySpark, Extract, Transform, Load (ETL), Data Warehouse Architecture, Apache Kafka, Tableau, Data Warehousing, Apache Spark, REST APIs, Snowflake Cloud, LangGraph, Elasticsearch, Data Build Tool (DBT), FastAPI, Grafana, TypeScript, AWS Lambda, AWS Step Functions, Amazon QuickSight
Experience

Data Engineer
Seattle, WA
Amazon Business • Restored query SLA compliance across 4 Redshift clusters by designing an idempotent Step Functions framework executing 600+ VACUUM and 3,200+ ANALYZE operations daily with retry logic, failure isolation, and throttle-aware execution. • Eliminated manual configuration and configuration drift by deploying the infrastructure via AWS CDK with IAM boundaries, observability, alerting, and per-cluster failure isolation for auditable, reversible operations. • Built QuickSight observability dashboards tracking VACUUM/ANALYZE completion rates, p95 query latency, and storage utilization, reducing on-call triage time from hours to minutes.

Software Engineer
Troy, Michigan, United States
• Built a LangGraph text-to-SQL agent that generates and validates Snowflake queries grounded in dbt schema metadata, with an error-feedback loop, served via FastAPI to enable analysts to self-serve data requests, reducing turnaround from days to minutes. • Built a Snowpipe ingestion pipeline with S3 event triggers achieving sub-5-minute data freshness into Snowflake, backed by dbt transformations, instrumented with Grafana metrics and ElasticSearch logs to surface ingestion lag and test failures.

Software Engineer | AR System Co., Ltd.
Tokyo, Japan
• Enabled daily e-commerce reconciliation and Tableau analytics for finance and ops stakeholders by orchestrating batch PySpark ETL pipelines via Airflow DAGs, processing high-volume workloads from ingestion to downstream consumption. • Cut Spark processing latency by 55% by profiling shuffle skew, partition sizing, execution plans and lowering compute costs. • Designed a star schema warehouse for e-commerce order analytics (order,sales facts, product/customer/time dimensions) supporting sub-second aggregation across 5TB+ of transactional data for business intelligence workloads. • Architected a microfrontend e-commerce platform using React and JavaScript, reducing initial page load by 65% and improving Core Web Vitals by 40% through lazy loading, efficient data fetching and tree shaking. • Built Python microservices deployed via Docker for order and inventory management, designing versioned RESTful APIs with OAuth, rate limiting, input sanitization, and structured error contracts, with near-real-time event propagation via Kafka. • Built GitLab CI/CD pipelines with blue-green deployments and expanded AAA-structured test coverage from 55% to 95%, adding pre-release translation drift detection that cut localization bugs by 30% before production.
Education
Aiswarya Vijaya Kumar's Contact Information
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