Lead data engineer for a fintech startup (YCombinator 2015)

RedCarpet lends where banks cannot see.

Some of the press around what we are doing is here:

- http://tech.economictimes.indiatimes.com/news/technology/yes-bank-taps-ai-to-directly-offer-small-loans-to-students/59484785
- https://www.yesbank.in/media/press-releases/10-start-ups-graduate-from-yes-fintech,-yes-banks-business-accelerator-program-for-fintech-start-ups
- https://yourstory.com/2016/05/google-launchpad-india-2016/
- https://youtu.be/xoZsNN9UGlQ?t=301 (Google Launchpad best startup feature)
- https://twitter.com/DIPPGOI/status/938345126526459905/photo/1 (showcased at GES innovation summit for the PMO)
- https://economictimes.indiatimes.com/small-biz/startups/newsbuzz/fintech-startup-redcarpet-collaborates-with-neostencil-to-provide-student-loan-for-premium-government-job-tuition-fee/articleshow/65245884.cms

We are a proud #MakeInIndia startup trying to disrupt a 2 trillion dollar space (yup.. that's how much credit/loans India needs to grow) while building some seriously deep tech. We work closely with the Niti Aayog, RBI, NPCI and the Startupindia/DIPP and contribute our policy papers and opinions on a highly regulated space like lending.

We have chosen to take a higher ethical ground through design, long before privacy concerns ever surfaced in India - https://www.redcarpetup.com/2017/11/29/design-for-honesty/

Life@RedCarpet - http://instagram.com/redcarpetuplife

Cultural Values - https://www.redcarpetup.com/jobs/

The Role

The Role:

Our fullstack tech stack uses Typescript, Reactjs, Redis, Celery, Flask, Python, Docker, Postgres and Scikit. You will also end up touching a whole bunch of ReactJs for our internal webapps.
We plan to build a stack that is scalable and builds on top of technologies like Kubernetes, PySpark, Luigi, AWS Lambda, Kafka, Gevent and Asyncio. We are looking for **you**
to architect that.

We were looking for someone to join us as our Lead Data Engineer and join us on this incredible adventure. 

Note: that this is a senior data engineering role. This is for someone who has already played with terabytes of data in a production facing role.  We have other roles for fresh graduates in analytics and data science. 

 
Important: our philosophy of datascience comes from the Google Brain team and the Imagenet teams. 

Google Brain - https://developers.google.com/machine-learning/rules-of-ml/
"Most of the problems you will face are, in fact, engineering problems. Even with all the resources of a great machine learning expert, most of the gains come from great features, not great machine learning algorithms".

Imagenet - https://qz.com/1034972/the-data-that-changed-the-direction-of-ai-research-and-possibly-the-world/

“One thing ImageNet changed in the field of AI is suddenly people realized the thankless work of making a dataset was at the core of AI research,”

You need to passionate about data - because that is the true value in a country like India. You should be truly excited about architecting pipelines like Uber Michaelangelo and Airbnb Bighead. You will work on Docker (for deployment), Typescript/React (to build usability around models), Airflow (for dependability), Apache Arrow (for persistence) and Apache Spark (for scalability). You will learn to love the Grammar of Graphics and work extensively in Bokeh, D3.js, Vega.

You will also share our dislike for Mongodb and respect for Postgresql !

We are on our way to build one of the finest data engineering stack in India. You're welcome to come and lead the effort here. 

Qualifications

Some of the most incredible programmers I’ve known don’t have pretty resumes, so we have no “minimum” requirements for degrees. We’re also hyper-equal-opportunity: quality work knows no bounds for race, gender, nationality, sexual orientation, or religion. If you love your work and breathe code, we’ll do amazing things together, no matter who, what, or where you are. We do put a very high premium on your past work - and especially your github and play store portfolio. Please do not forget to send that in.