We are on a mission to rid the world of bad customer service by “mobilizing” the way customer service is delivered. Today’s consumers want an always-available customer service experience that leaves them feeling valued and respected. Helpshift helps brands deliver this modern customer service experience through a mobile-first approach. We have changed how conversations take place, moving the conversation away from a slow, outdated email and desktop experience to an in-app chat experience that allows users to interact with brands in their time. Through our market-leading chatbots and automation, we help brands deliver instant and rapid resolutions. Because agents play a key role in delivering help, our platform gives agents superpowers with automation and AI that simply works. Companies such as Brex, EA, Square, Tencent, Supercell, and hundreds of leading brands use the Helpshift platform to mobilize customer service delivery. Over 820 million active monthly consumers are enabled on 2B+ devices around the world with Helpshift.

Some numbers that illustrate our scale:

85k/rps

30ms response time

300 GB data transfer/hour

1000 VMs deployed at peak

About Dataplatform team -

Consumers care first and foremost about having their time valued by brands. Brands need insights into their customer service operation to serve their consumers effectively. Such insights and analytics are delivered through various data products like in-app analytics dashboards and data-sharing integrations.

The data platform team is responsible for designing, building, and maintaining the data infrastructure that enables such data products at scale. We build and manage data pipelines, databases, and other data structures to ensure that the data is reliable, accurate, and easily accessible. We also enable internal stakeholders with business intelligence and machine learning teams with data ops. This team manages the platform that handles 2 Million events per minute and processes 1+ terabytes of data daily.

About Role -

• Building maintainable data pipelines both for data ingestion and operational analytics for data collected from 2+ billion devices and 900M Monthly active users
• Building customer-facing analytics products that provide actionable insights and can easily detect anomali