Anuska Shrestha

I’m a Data Engineer / Data Analyst with 5+ years of experience building scalable data platforms and delivering actionable insights across financial and manufacturing domains. I focus on translating complex business requirements into high-performance, governed data solutions that teams can trust.

In my most recent role, I designed and implemented a domain-oriented lakehouse architecture consolidating trading, liquidity, and risk datasets into governed analytical layers using Databricks and Snowflake. I built event-driven ingestion pipelines with Kafka and Spark Structured Streaming, then developed advanced analytical datasets with SQL and PySpark to support P&L analysis, capital adequacy modeling, and stress testing.

I partner directly with risk, treasury, and analytics stakeholders to turn regulatory and trading requirements into scalable data transformations and curated reporting tables. I also run deep data profiling and root-cause analysis to identify upstream gaps, and I strengthen reliability with automated data validation using dbt tests and custom Python checks.

I bring strong cloud and engineering discipline to analytics delivery—CI/CD and Infrastructure-as-Code with Terraform and GitHub Actions, performance tuning across Databricks clusters, and security-by-design with IAM/RBAC, encryption, and data masking. I also leverage Generative AI tools like GitHub Copilot, AWS Bedrock, and LangChain to accelerate transformation development, documentation, and data exploration.