Anish Pokharel

Senior Data Engineer with over 7 years of experience turning large scale, complex data into reliable platforms that healthcare, insurance, and retail teams can trust. Designs and optimizes batch and streaming ETL/ELT pipelines built on Apache Spark, Kafka, Apache Airflow, and dbt, with a strong focus on data modeling, data quality, and data governance that keep systems healthy well beyond launch. Much of this recent work centers on modern lakehouse architectures and on migrating legacy ETL into cloud native pipelines across Azure, AWS, and GCP as well as Snowflake and Databricks. Beyond the engineering itself, leads migration initiatives and mentors junior engineers, helping them grow in pipeline design, performance tuning, and governance. More recently, the focus has shifted toward the data infrastructure behind AI, including building Retrieval Augmented Generation (RAG) pipelines with embedding workflows, vector search, and LLM integration for real enterprise use cases rather than demos. Because this work consistently involves sensitive healthcare and financial data, security, HIPAA compliance, and governance are treated as design principles from day one rather than afterthoughts. Works most effectively alongside analytics, security, ML, and compliance teams, translating between them to ship data platforms that hold up in production.