Naresh .

Project 1: Sr Data Engineer – Fidelity Investments Duration: Apr 2024 – Present Cloud: Google Cloud Platform (GCP) Real-Time Scenario: 401(k) Retirement Plan Data Platform Designed and maintained a real-time 401(k) data ingestion platform processing contribution, allocation, and transaction events from employer payroll systems. Built streaming pipelines using Pub/Sub to capture live participant contributions, employer matches, and fund rebalancing events. Implemented data transformations and validations in Dataflow to ensure compliance with retirement plan rules and IRS regulations. Stored curated datasets in BigQuery to support real-time reporting on participant balances, vesting status, and plan performance. Enabled downstream analytics for plan administrators, compliance teams, and customer-facing dashboards. Improved data availability SLAs for 401(k) transactions during market volatility and payroll peak cycles.

Project 2: Full Stack Engineer – Citi Duration: Dec 2022 – Apr 2024 Cloud: Microsoft Azure Real-Time Scenario: Banking Transaction Risk & Monitoring Built data pipelines to process real-time card and account transactions for fraud and risk monitoring. Ingested high-frequency transaction events using Azure Event Hubs. Developed enrichment and aggregation workflows in Azure Databricks to compute rolling risk indicators. Persisted transactional and derived datasets in Azure SQL / Data Lake for regulatory reporting. Supported compliance and fraud teams with near-real-time insights into abnormal transaction patterns.

Project 3: Machine Learning Engineer – Employbridge Duration: Oct 2021 – Dec 2022 Cloud: AWS Real-Time Scenario: Staffing & Workforce Analytics Built a real-time candidate matching and demand forecasting pipeline for staffing operations. Processed live applicant data and job postings through streaming ingestion workflows. Trained and deployed ML models using AWS SageMaker to score candidate-job fit. Stored feature data in S3 and delivered predictions with low latency to recruiter tools. Improved placement speed and reduced manual screening efforts.

Project 4: Data Engineer – AT&T Duration: Nov 2020 – Oct 2021 Cloud: Microsoft Azure Real-Time Scenario: Telecom Network Usage & Performance Analytics Designed streaming data pipelines to capture real-time network usage and device telemetry. Used Azure Event Hubs to ingest high-volume call, data, and signal events. Processed streams using Azure Databricks to generate network performance KPIs. Stored processed data in Azure Data Lake for operational and capacity planning analytics. Enabled network teams to identify congestion and service degradation faster.

Project 5: Java Developer – Walmart Duration: Jul 2018 – Nov 2020 Cloud: AWS Real-Time Scenario: Retail Inventory & Supply Chain Data Developed data services to track real-time inventory movement across stores and warehouses. Processed sales and return events to update stock levels with minimal latency. Used AWS Lambda to handle event-driven inventory updates. Stored high-throughput inventory data in DynamoDB for fast lookup. Supported replenishment and demand planning systems during peak retail seasons.

Project 6: J2EE Consultant – Nuscsoft Duration: Jan 2013 – Dec 2015 Cloud: AWS Real-Time Scenario: Enterprise Order & Billing Systems Worked on enterprise-scale order processing and billing platforms. Built batch and near-real-time data flows for invoice generation and payment reconciliation. Optimized backend data access for high-volume transactional systems. Supported operational reporting for finance and audit teams.