Lead Data Analyst
Zilingo
Bangalore
3d ago

About Zilingo

Zilingo is an online marketplace established in 2015 with a focus in fashion and lifestyle. Founded by former Mckinsey consultant Ankiti Bose, and ex-

Yahoo engineer Dhruv Kapoor, Zilingo is an online marketplace established in 2015 with a focus in fashion and lifestyle.

An insight to our remarkable growth :

Having our offices in 7 countries (Thailand, Singapore, Indonesia, Hong Kong ,India, Philippines, New York), we have seen explosive but sustained growth since our inception, becoming one of the largest and fastest growing e-

commerce marketplaces in Southeast Asia. We host over 25,000 SMEs across Indonesia, Singapore, Thailand, China, Hong Kong, Vietnam and Taiwan with a reach of more than a million customers per month.

Our businesses include B2C & B2B Marketplace, Private Label as a Service, E-POS & Inventory Management, Trend Forecasting and Fintech.

Each business complements the other, creating compounding benefits for the platform.

Completing our Series D round of funding recently (coverage on Techcrunch, Yourstory, Inc42, and more), we leap forward to the next level of growth, products, and new ventures.

We’re actively looking to hire the world’s best talent to join us. If you have the passion and ambition, let’s build the next big thing together!

The data warehouse stack is Impala SQL engine over Kudu (Cloudera Hadoop). The visualization (dashboards), and reporting service is run on top of it, and the stack allows for quickly plugging in any required analytic tools such as R or Spark.

Additionally, Impala is an MPP (massively parallel processing) SQL engine built for real-time querying on large data sets, which means data analysts can generally get results from complex queries in seconds, and thus can interactively iterate and explore data.

Data analytics is at the center of many fast-scaling, new, and diverse projects at Zilingo. The data analytics team works closely with tech, product, data science, and business teams on a diverse set of problems, including marketing, product cohorts, product features, operations, and customer segmentation.

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