Data Science
Core Areas: Understanding business objectives and defining the problem statements, goals and approach. Leading the team on non-trivial problems in terms of choosing the right frameworks and tech stacks. Managing changing stakeholder requirements/expectations along with pace of the project executions. Ability to communicate with technical and non-technical audiences with ease.
Qualification: Experience: 8+ Years
8-10 years of IT experience with 3+ years of Data Architecture experience in Data Lake
Good Experience in Informatica & Snowflake
Our Story
Zepto is a fast-growing startup that delivers groceries in 10 minutes through an optimized network of dark stores that we're building across the country!
We’re incredibly well-funded and our investors include Y Combinator, Glade Brook, Nexus Venture Partners, and more! We’ve also built out one of the best startup teams in India, with Senior Executives from Uber, Flipkart, Dream11, and institutions like Stanford, INSEAD, IIM, and IIT
Analytics is mission critical to Zepto, serving as the source of truth for the entire organization. You will be working closely with leadership across attempting to answer questions like where to put up our dark stores, forecasting demand across products at a hyperlocal level, designing incentives for last mile, optimizing marketing spends and margins. If tackling hard problems, challenging conventional wisdom and working in a rapidly evolving environment excites you, we would love for you to join us on our journey.
About the organization:
Client is a new age startup working on Dark Store business model delivering groceries in less than 10 mins with a vision to be the first choice of groceries. Being valued at 570 Mn $ they are aiming to reach their Unicorn status in less than 1yr to be the youngest Unicorn startup of India.
The data engineering team closely works with the Technology and Analytics team to design, propose and develop solutions keeping the growing scale & business requirements in mind. Looking for a leader who shall own, define and execute the overall data engineering practice vision.
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