Naga Lakshmi N

Data Engineer with 3+ years of experience delivering production-grade data pipelines, real-time streaming systems, and ML-ready infrastructure across finance and enterprise environments — currently at JP Morgan in New York. I design and own end-to-end data systems that power analytics, machine learning, and business intelligence at scale. My pipelines handle millions of records daily, integrating heterogeneous data sources into clean, reliable, and actionable datasets for cross-functional teams. Core expertise: • Real-time streaming — Apache Kafka, Spark Streaming, GCP Pub/Sub • Pipeline orchestration — Apache Airflow, AWS Glue, GCP Dataflow • Cloud platforms — AWS (S3, Glue, Redshift, SageMaker, EMR) | GCP (BigQuery, Pub/Sub, Dataflow) | Azure (Synapse, Data Factory) • ML infrastructure — MLflow, SageMaker, feature engineering, model productionalization, drift monitoring • Data quality — schema validation, anomaly detection, reconciliation frameworks • Languages — Python, SQL, PySpark, Scala, Bash Previously at LTIMindtree, I built large-scale Spark and Kafka pipelines, migrated Hadoop workloads to AWS and Azure, and delivered curated datasets supporting BI and ML teams across enterprise clients. ndustries I've supported: Financial Services · Healthcare Data Compliance (HIPAA/GDPR) · Enterprise Analytics Open to Data Engineer and ML Data Engineer opportunities across finance, retail, automotive, healthcare, and tech. 🎓 MS Data Science — University at Buffalo 🏅 AWS Certified Machine Learning Engineer — Associate