The thrill of working at a start-up that is starting to scale massively is something else.

Simpl is the payment platform for the mobile-first world, and we’re backed by some of the best names in fintech globally (folks who have invested in Visa, Square and Transferwise), and has Joe Saunders, Ex Chairman and CEO of Visa as a board member. 

Everyone at Simpl is an internal entrepreneur who is given a lot of bandwidth and resources to create the next breakthrough towards the long term vision of “making money Simpl”.

Our product is a payment platform that lets people buy instantly, anywhere online, and pay later. In the background, Simpl uses big data for credit underwriting, risk and fraud modelling, all without any paperwork, and enables Banks and Non-Bank Financial Companies to access a whole new consumer market.

Responsibilities

You will be focused on making sure of how we store, secure, process and manage data from millions of users using our platform. You should be a star athlete who knows everything about data pipelines, RDBMS, Kafka, transactions and handling data for millions of active users per day.

We need someone who has already built scalable, high performance data intensive services. 

Examples: 

- How do you store transactions for millions of users in Postgres? How do you design tables in RDBMS with billions of rows in a single table? How do re-architect to handle 10x more load in the next 18 months?

- We have data pipelines processing aggregate and statistical data. Should we store this in Redshift, in flat files in S3, or somewhere else? How do you work with Data Science team to avoid massive redundancy of data at multiple places in the stack?

-  We need to track various data points to identify our customers in various locations, including from different devices, and determine that two seemingly disparate users are actually the same. How can we do this efficiently and effectively? How do you write code that can do this a few millions time per hour?