Himanshu shukla

• Managed large-scale marketing & campaign data pipelines supporting 3 Mastercard clients across 4+ countries • Built automated data ingestion frameworks using Spark, Adverity, Google Ads API, and Meta API, enabling scalable and reliable marketing data integration • DDesigned optimized PostgreSQL data models powering downstream BI dashboards & MMM use cases. • Delivered analytics-ready datasets powering data science & marketing mix modeling (MMM) initiatives • Collaborated cross-functionally with BI & DS stakeholders to improve reporting accuracy, data usability, and pipeline reliability.

• Deployed 10+ Databricks Spark/Kafka pipelines processing 4TB/day from collection to storage, handling complex transformations with 99.9% uptime. • Developed systems to manage 10 million daily network alerts using Kafka message queues and Spark processing, storing results in MySQL to coordinate field technician assignments for 55,000 support staff • Designed stateful notification service leveraging Redis Sorted Sets for deduplication and Kafka exactly-once semantics, achieving 99.92% measured delivery rate across 150K SMS/WhatsApp alerts per minute during peak outages • Devised automated data quality checks in Azure Databricks to detect anomalies in critical network KPIs, reducing customer complaint escalations by 15% through early issue identification and proactive resolution. • Configured Azure Data Factory pipelines to migrate data from HDFS to Azure Blob Storage, improving data processing speeds by 30% due to optimized cloud storage. • Redesigned Spark jobs (partitioning, broadcast joins) cutting pipeline costs by 20% and Improved SLA adherence by 10%