Gnanasambandham Balasundaram

I am an experienced Data Engineer with deep expertise in designing scalable ELT pipelines, cloud-native data platforms, and analytics solutions for high-risk financial environments. I currently work on anti-financial crime initiatives at NatWest, focusing on secure, high-performance, and cost-efficient architectures using Snowflake, AWS, and Python.

I have led large-scale migrations and platform builds, including migrating 1,000+ tables from Teradata to Snowflake and delivering reusable, auditable data assets supporting AML, sanctions, and fraud detection. My work emphasizes data modelling (Star, Snowflake, Data Vault), governance, role-based access, and automation to ensure compliant and reliable data delivery.

Technically, I build large-scale PySpark pipelines, automated DQ frameworks, and event-driven AWS solutions (Lambda, S3, Step Functions, DMS), and I have implemented dbt-based transformation frameworks, Kafka streaming ingestion, and CDC strategies. I collaborate closely with risk, legal, compliance, and ML teams to convert business typologies into robust data logic and improve alert precision.

I deliver measurable results: reduced manual effort for DQ by 70%, accelerated migrations and processing times, and improved data processing speed and reliability across enterprise FinCrime platforms. I bring an outcome-oriented, compliance-first approach to data engineering in regulated financial settings.