Khaleda Khanam

About Khaleda Khanam

Lead Data Engineer with 12+ years of experience delivering robust, scalable, and secure data engineering solutions across banking, healthcare, retail, life sciences, and insurance sectors. I specialize in building high-performance data pipelines using Databricks, Spark, PySpark, Python, SQL, and modern orchestration tools like Airflow and Azure Data Factory, across cloud platforms: AWS, Azure, and GCP. I’ve successfully led enterprise-scale projects involving real-time streaming (Kafka, Event Hubs), large-scale batch processing, Delta Lake design, and medallion architecture. I bring deep expertise in data governance, quality frameworks, and automated validation to ensure complete, accurate, and audit-ready data for business-critical use cases. My work has enabled regulatory compliance, enhanced self-service analytics, and empowered executives, finance, and marketing teams to make informed decisions with confidence. I’ve worked with cross-functional teams to design and implement cloud-native data lakes, metadata-driven ETL frameworks, modular processing layers, and governed access through Purview, Data.World, and Unity Catalog. My goal in every engagement is to deliver pipelines that are resilient, observable, secure, and easily extensible — always production-ready, never PoC-bound. I thrive in fast-paced environments where performance, cost-efficiency, governance, and business alignment are not negotiable — and my deliverables reflect that.

Experience

1. Lead Data Engineer Architect

   Hewlett Packard Enterprise

   Mar 2025 — Present · US

   Built and deployed scalable Spark-based pipelines using Databricks on Azure; led cataloging and data lineage implementation via Data.World, integrated with Power BI, delivering enterprise-grade reporting across Finance and Claims.