Rahul N

About Rahul N

Results-driven Network Core Engineer with 5+ years of experience supporting telecom and…

Experience

1. Python Developer

   Citi

   Jan 2025 — Present · US

   Developed scalable Python adapters integrated with Ansible and REST APIs to automate networkprovisioning and configuration tasks, reducing manual intervention and enabling faster deploymentsacross telecom infrastructure with high consistency and reliability.• Built custom Python monitoring scripts to detect anomalies in real-time network traffic patterns, triggeringKafka-based alerts for faster incident response and enhancing visibility into performance bottlenecksacross telecom systems.• Designed and developed scalable ETL pipelines using PySpark and AWS S3 to process large volumes ofbanking transaction data with high reliability and fault tolerance.• Built distributed data processing solutions on AWS EMR using Spark to analyze fraud patterns, optimizeAML workflows, and ensure compliance reporting.• Collaborated with data scientists and analysts to implement complex data transformation logic usingPySpark DataFrames and SQL for regulatory reporting and performance KPIs.• Integrated Kafka with Spark Streaming to process real-time transaction streams, monitor suspiciousactivities, and trigger alerts for AML teams.• Developed automated ETL workflows using Airflow and Python, improving pipeline reliability andreducing job failures by 30%.• Optimized PySpark jobs through partitioning, caching, and broadcast joins, reducing job runtimes by over40% for batch ingestion of trade and compliance logs.• Wrote modular and reusable Python components for batch and streaming data ingestion, leveraging SparkStructured Streaming and AWS Lambda for real-time use cases.• Ingested data from external banking APIs and internal SQL sources into Delta Lake on Databricks,building a lakehouse architecture for scalable insights.• Participated in data quality checks, schema validation, and unit testing of Spark pipelines, ensuring highavailability and accuracy in production workloads.• Provided ad-hoc analytics support to finance and operations t