Sowjanya Jalubula

Data Engineer @Cliff Services Inc

US

Designed scalable Snowflake data pipelines processing multi-terabyte banking datasets. Applied materialized views, clustering keys, and partition pruning to reduce query latency by 60% and lower compute/storage costs.Enhanced SQL performance for complex transformations and aggregations using CTEs, window functions, and indexing strategies, improving both real-time and batch job efficiency by 70%.Architected enterprise-grade data warehousing solutions using Snowflake and AWS S3, implementing zone-based architecture (raw, staged, curated) to support governed, scalable reporting for finance and compliance.Built big data processing frameworks using Apache Spark SQL and Hive on EMR, enabling distributed processing of billions of transactions (credit card, wire, fraud logs) with audit compliance and fault tolerance.Developed robust Delta Lake pipelines using AWS Glue and Databricks, with ACID compliance, schema validation, and time-travel support to streamline regulatory analytics and data science use cases.Automated ETL pipelines with AWS Glue, Lambda, and EventBridge, integrating metadata-driven orchestration for auto-scaling, error handling, and lineage tracking—reducing manual effort by 90%.Built high-throughput real-time ingestion frameworks in Python using asyncio, aiohttp, and multiprocessing, capable of ingesting over 100K records/min from financial APIs and market feeds.Engineered a real-time streaming platform using Apache Kafka and Spark Structured Streaming, capturing sub-second financial events (ATM, payments, logins) to power fraud detection models and real-time dashboards.

Vignan's Foundation for Science, Technology & Research

Bachelor's degree, Electrical, Electronics and Communications Engineering

Kennesaw State University

Master of Science - MS, Computer Science