Amish Agrawal
- Role
- Senior Lead Engineer Senior Data Engineer at Airtel Digital
- Location
- Gurugram, IN
- LinkedIn followers
- 500 followers
About Amish Agrawal
10 years of Backend engineering experience in building scalable distributed systems…
Experience
Senior Lead Engineer Senior Data Engineer
Feb 2021 — Present
Leading development of the Acquisition Platform for D2C Platform.\\\\n\\\\n1) Activity Manager & Agent Tracking Feature :\\\\n- Agents can be tracked on real time and their performance will be updated immediately which results in better utilisation. Designed & developed module that enables managers to assign multiple tasks and customer calling data (matchmaking basis location etc.) to it\'s reporters along with tracking current activity status capabilities. This feature resulted in better lead allocations (~30%) and faster actions (multiple hours to under 30 min).\\\\n\\\\n2) Proximity Based Allocation :\\\\n- Features which enables better allocation of leads to agents which is located nearest to customer. This feature resulted in better allocation of leads, faster response time to customers, better resource utilisation. Using Geo location based lead allocation to increase lead conversion to acquisition. Directly impacting the increase in business for Airtel across multiple LOBs.\\\\n\\\\n\\\\nLeading development of a Self Serve Platform for Real-Time Analytics and Data Science.\\\\n\\\\n- Developed a generic LOB agnostic pipelines to calculate metrics in real-time for dash-boarding. Handling data of 80M+ records and ingress of data which is passed through pro-active calculation of all required KPAs.\\\\n- Handling the data engineering, reporting, analytics dashboards, alerts and data science solutions across all LOBs for the Workforce Management platform.\\\\n- Involved in Design discussion to constantly modify the architecture and building a resilient and scalable system using open source technologies like Java, Spring Boot, Micro-services Arch, Apache Superset, Apache NiFi, Apache Kafka, Apache Flink, Kafka Connect, ELK stack.\\\\n- Built a highly scalable and robust data pipeline with multiple sources/channels/Sinks which processes millions of Kafka events per day and persistent them in different sinks. Different source/channels/sinks refer to: Kafka/RabbitMQ/PostGre/Redis/Elastic Search/Cassandra.\\\\n \\\\n\\\\n \\\\n \\\\n\\\\n \\\\n
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