Arunoday Singh

Software Engineer

Gurugram, Haryana, India2 yrs 4 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in building scalable data pipelines using Snowflake.
Automated workflows to enhance operational efficiency.
Proficient in real-time data processing and reporting.

Stackforce AI infers this person is a SaaS-focused Software Engineer with expertise in cloud data solutions and automation.

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Skills

Core Skills

Cloud ComputingData Pipeline DevelopmentAutomation & Workflow OrchestrationData Management

Other Skills

API Development & IntegrationAmazon Web Services (AWS)AppsFlyerArtificial Intelligence (AI)Backend DevelopmentC++Computer ArchitectureData Structures & Algorithms (DSA)Database Management (SQL & NoSQL)DockerExpress.jsFlaskFull-Stack DevelopmentGCPGoogle Ads API

Experience

2 yrs 4 mos

Total Experience

2 yrs 4 mos

Average Tenure

2 yrs 4 mos

Current Experience

Wpp media

Software Engineer

Jan 2024 – Present · 2 yrs 4 mos · Gurugram, Haryana, India · On-site

🔧 Data Enrichment Pipeline using Snowflake
Built a scalable pipeline using Snowflake for seamless integration with S3 and GCP.
Leveraged external tables and secure sharing to enable real-time data processing.
Optimized workflows using Snowflake’s native connectors, encryption, and role-based access controls for secure data management.
Implemented Snowflake’s advanced features like Time Travel and Zero Copy Cloning for efficient analytics.
⚙️ Wrike Approval Workflow Automation
Automated end-to-end approval workflows using the Wrike API.
Integrated Power Apps, SharePoint, and Power Automate to improve collaboration and streamline processes.
📊 Automated Reporting to Avoid Manual Effort
Automated daily data extraction using the Google Ads API, eliminating the need for third-party platforms.
Pushed data to S3 for storage and used Power BI to build real-time reporting dashboards directly from the data, minimizing manual reporting tasks.
🔧 Data Pipeline Development
Developed a seamless ETL pipeline to transfer data from SharePoint to GCP.
Utilized Power Automate, Node.js, Docker, and Cloud Run for scalability and efficiency.