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VIKAS GUPTA

Consultant

I am a Consultant with 3 years of experience at Capgemini, where I enhanced operational data accessibility by 36% through the implementation of optimized workflows. I take pride in my work on the Event-Driven Data Pipeline and Telemetry Processing Framework, which streamlined data processing and significantly improved efficiency. As I deepen my expertise in scalable analytics and customer-facing reporting solutions, I am excited to tackle more complex challenges that drive impactful business outcomes.

Skills

PythonSQLRESTful APIsWebhooksData Pipeline DevelopmentEvent-Driven IngestionStructured & Unstructured Data ProcessingETL/ELT WorkflowsData TransformationPipeline OptimizationMicrosoft FabricPower PlatformCloud-Based Analytics EnvironmentsRelational DatabasesCloud Data IntegrationScalable Data WorkflowsOperational Data ProcessingDistributed Data PipelinesStreaming Data ProcessingEvent-Driven WorkflowsWorkflow OrchestrationAirflow-Style OrchestrationPrefect-Style SchedulingPipeline MonitoringWorkflow AutomationOperational Workflow ManagementData ValidationSchema ValidationData Integrity MonitoringAnomaly DetectionPipeline ObservabilityAutomated Recovery MechanismsPerformance OptimizationOperational Reliability ImprovementGitCI/CD PracticesDocker-Style ContainerizationJiraConfluenceBitbucketAgile DevelopmentTechnical DocumentationCross-Functional Engineering CollaborationIntegration Logic DocumentationCustomer-Facing Reporting DatasetsOperational AnalyticsIoT-Style & Telemetry Data ProcessingRF/Network-Connected Data WorkflowsScalable Reporting InfrastructureData Accessibility & Governance

Projects

Event-Driven Data Pipeline & Telemetry Processing Framework

Engineered scalable Python- and SQL-based ingestion frameworks processing REST API payloads, webhook events, and telemetry-style operational data streams across cloud-connected analytics environments handling 150K+ records daily. Built orchestration-ready ingestion and processing logic supporting event-driven workflows, automated schema validation, and scalable downstream data availability for operational monitoring and customer-facing systems. Implemented pipeline observability, anomaly detection, and automated recovery mechanisms reducing recurring workflow disruptions by 41% and improving reliability of high-volume ingestion operations.

Cloud Infrastructure & Data Workflow Automation Initiative

Developed cloud-based ingestion and workflow automation processes using Microsoft Fabric-style environments, Power Platform integrations, Git-based version control, and CI/CD-oriented deployment practices supporting scalable analytics engineering operations. Supported containerized workflow execution and orchestration initiatives using Docker-style runtime environments and Agile collaboration workflows aligned with Jira/Confluence-style engineering ecosystems. Optimized ingestion scalability, pipeline monitoring, and multi-source workflows to improve maintainability and performance.

Experience

Capgemini

Apr 2021 - Aug 2024

Developed scalable Python- and SQL-based data pipelines integrating RESTful APIs, webhook-driven ingestion workflows, and cloud-connected operational datasets supporting enterprise analytics across 3 cross-functional initiatives. Built and optimized ingestion, transformation, and orchestration workflows using Microsoft Fabric-style environments, Power Platform integrations, and structured processing pipelines improving scalability, reliability, and operational data accessibility by 36%. Monitored and maintained API integrations, pipeline performance, cloud-based data workflows, and SQL environments while supporting troubleshooting, data quality initiatives, and operational system reliability improvements. Collaborated with engineering and operational stakeholders using Agile delivery practices, Git-based version control workflows, and CI/CD-style deployment coordination to support scalable analytics and customer-facing reporting solutions.

Maeve Therapy

Jul 2020 - Jul 2023

Designed Python- and SQL-driven transformation workflows processing 58K+ operational and engagement records from structured and unstructured reporting systems supporting scalable operational analytics initiatives. Developed automated validation logic, API-driven exports, and multi-source integration processes improving consistency, usability, and reliability of recurring analytical datasets and operational reporting outputs. Supported workflow optimization initiatives by identifying ingestion bottlenecks, improving transformation efficiency, and streamlining recurring data processing activities across cloud-connected reporting environments. Documented data schemas, transformation logic, and operational workflows while supporting iterative enhancements, cross-functional collaboration, and ongoing analytics delivery in Agile environments.

Education

University of Florida, Warrington College of Business

Master of Science in Information Systems and Operations Management (Data Science)Apr 2026

University of Mumbai

Bachelor of Engineering in Information TechnologyOct 2020

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