Rahul Maloth

About Rahul Maloth

I am a Data Engineer with over 3.5 years of experience specializing in the design, migration, and optimization of scalable data lakehouses and serverless pipelines across GCP and AWS. My career is defined by a commitment to transforming complex legacy environments into high-performance, cloud-native ecosystems that drive real-time business intelligence and actionable insights.On the GCP front, I currently work on large-scale migrations from Oracle Exadata to BigQuery at Verizon, where I have improved query performance by 35% through strategic partitioning and refactored SQL. My work involves engineering Python-based DAGs in Cloud Composer (Airflow) to automate complex workflow orchestration and utilizing Dataflow to ensure 100% data integrity for billions of records.My AWS expertise is highlighted by my work at HealthStream, where I design serverless data pipelines using AWS Lambda to process over 1M transactions monthly, improving decision-making speed by 30%. Previously, at Talestry, I leveraged AWS Glue and Redshift to reduce processing times on terabytes of data while utilizing Databricks and Kubernetes to achieve $0.3M in annual cost savings.Beyond infrastructure, I have a deep background in AI from my time at STL, where I spearheaded the lifecycle of computer vision products using Deep Learning models like BERT and LSTM. This technical breadth is supported by a Master’s in Advanced Data Analytics from the University of North Texas and a B.Tech from IIT Kharagpur, combining a rigorous academic foundation with proven industry impact.

Experience

1. Data Engineer

   Infinite Computer Solutions

   Nov 2025 — Present · Dallas, TX, US

   Client: Verizon• Cloud Migration: Executing the end-to-end technical migration of high-volume network datasets from legacy Oracle Exadata environments to Google Cloud Platform (GCP), ensuring structural integrity and logic parity within the target BigQuery architecture.• Lineage Automation: Developed and deployed custom PL/SQL automation scripts to programmatically identify and document data lineage for complex Oracle tables, reducing manual discovery efforts and ensuring 100% metadata transparency during the migration phase.• SQL Optimization: Refactored legacy Oracle SQL procedures into optimized BigQuery Standard SQL, implementing strategic partitioning and clustering that improved query execution performance by 35% for downstream analytics.• Workflow Orchestration: Engineered and managed Python-based DAGs in Google Cloud Composer (Airflow) toautomate the scheduling, invocation, and dependency management of complex data pipelines, achieving high reliability for daily network reporting.• CI/CD Engineering: Designed and maintained Jenkins deployment pipelines and utilized Git for version control,streamlining the promotion of configuration files (YAML, Shell, JSON) across development & production environments.• Data Governance: Built automated classification scripts to scan migrated BigQuery tables for PII and sensitive network information, accelerating the enterprise governance approval process and ensuring compliance & security standards.• Ingestion & CDC: Configured and optimized Fivetran connectors and Change Data Capture (CDC) mechanisms to synchronize on-premise Oracle data with the GCP data lake, providing near real-time data refreshes for executive-level reporting.• Analytics Enablement: Collaborated with reporting teams to engineer analytics-ready data models in BigQuery,facilitating the seamless generation of Tableau dashboards for end-users and improving organizational decision-making speed.

Education

• University of North Texas

  Master of Science, Advanced Data Analytics

• Indian Institute of Technology, Kharagpur

  Bachelor of Technology, Electronics and Electrical Communications Engineering