Lakshmi Bodipudi

Senior Data Engineer @Truist

US

At Truist Financial, I architect and deliver enterprise-scale, high-throughput, low-latency data platforms powering fraud detection, risk scoring, and transaction monitoring. Leveraging Azure Databricks, Synapse, Data Lake, and PySpark, I design scalable lakehouse architectures, real-time streaming pipelines, and AI/ML-ready data ecosystems, enabling actionable insights and intelligent decision-making across business domains.I lead the design and implementation of distributed data architectures, including real-time graph processing pipelines in TigerGraph, ensuring seamless integration of batch and streaming workloads. By establishing robust ETL/ELT frameworks, data modeling standards, and architectural best practices, I drive consistency, scalability, and long-term platform reliability. I also automate infrastructure and deployment using Ansible, ARM templates, and Azure DevOps, ensuring secure, resilient, and highly available cloud environments.Partnering with business, analytics, and engineering teams, I translate complex requirements into scalable, production-grade data solutions while optimizing multi-terabyte and time-series datasets for performance, cost efficiency, and reliability. With expertise in Hadoop, Spark, Hive, Kafka, SQL Server, TimescaleDB, Docker, and Kubernetes, I establish enterprise data governance, lineage, and metadata management frameworks to support analytics readiness and regulatory compliance.By modernizing legacy systems into cloud-native, event-driven architectures, enhancing query performance, and enabling predictive analytics using Python, I deliver measurable business impact, operational efficiency, and future-ready data platforms—positioning Truist for data-driven innovation and advanced analytics at scale.