Gagan Arora

About Gagan Arora

Passionate DevOps Engineer with Expertise in Cloud Infrastructure and Automation | Leveraging Azure, GitHub Actions, and PowerShell to streamline service delivery and optimize resource utilization. Let\'s revolutionize your operations!#DevOps #Cloud #AutomationDevOps Enthusiast: Passionate about leveraging cutting-edge technologies to revolutionize IT operations and delivery efficiency.Automation Advocate: Driving automation initiatives across the board, transforming resource management and accelerating workflows.Innovative Problem Solver: Crafting solutions that span from automating server decommissioning to orchestrating onboarding of critical DevOps tools.Agile Implementer: Seamlessly adapting to diverse requests, from updating Sentinel versions to creating data-rich governance dashboards.Azure Cost Efficiency Specialist: Expertly optimizing Azure costs by architecting an automated solution for snapshot and backup management.Data Pipeline Architect: Pioneering AI/OPS pipelines with Databricks, enhancing monitoring through Terraform and New Relic integration.Collaborative Partner: Thriving in cross-functional environments, collaborating with teams to ensure seamless integration and delivery.Strategic Insight Provider: Enabling stakeholders with actionable insights through dynamic governance dashboards, enhancing decision-making.Continuous Learner: Committed to staying at the forefront of DevOps methodologies and emerging technologies.Let\'s connect to explore how my expertise in DevOps can contribute to your team\'s success.

Experience

1. Lead System Engineer

   EPAM Systems

   Jul 2025 — Present · IN

   Project: Customer Data AnalysisOverview:Designed and deployed an end-to-end customer call analytics pipeline using Amazon Transcribe Live Call Analytics (LCA) and Post Call Analytics (PCA) across multiple AWS accounts.Key Responsibilities & Achievements:Live Call Analytics (LCA):Deployed and configured LCA stacks via CloudFormation for real-time transcription of live customer calls.Built region-specific deployments using publish.sh and automated multi-account stack publishing.Integrated with Avaya call recordings → real-time transcription → S3 → downstream sentiment & category detection.Troubleshot mono audio ingestion and category detection issues.Post Call Analytics (PCA):Automated PCA deployment via CLI and CloudFormation; linked with LCA output S3 buckets for post-call analytics.Supported both raw audio and pre-transcribed JSON inputs.Enabled call categorization, redaction, entity detection, and sentiment analysis with PCA outputs visualized in QuickSight.Built parallel S3 upload scripts (Python & PowerShell) for 5k–10k recordings with deduplication logic for ANI/SID.End-to-End Data Flow:Avaya Telephony → S3 → LCA (real-time transcription) → PCA (analytics) → QuickSight dashboards.Key Learnings & Deliverables:Automated multi-account, multi-region CloudFormation deployments.Validated audio format compatibility (mono/stereo, WAV, JSON).Improved ingestion throughput and ensured data consistency with deduplication and parallel uploads.Strengthened operational efficiency and scalability across AWS environments.

Education

• JAI PARKASH MUKAND LAL INNOVATIVE ENGINEERING AND TECHNOLOGY INSTITUTE

  Bachelor of Technology - BTech, Computer Science