Data Pipeline Architect

This role requires writing optimised and scalable Advanced SQL, Python codes and scripts with

quick debugging skills. At a fundamental level, the responsible person should be able to dive

deep into a problem statement and extract interesting insights as well as solutions. In addition to

being a quick learner, this person is expected to get involved in active research projects with a

view to publishing them. Being in a startup, playing with the production environment should be like

a walk in the park

About The Team :

The Data-Tech team is primarily responsible for the solution of business-related problems by

upscaling through automation. Here, we focus on creating robust systems using the latest

technological tools and continuous research, just like a R&D Department. The team consists of a

handful of ecopreneurs wearing multiple hats of a Business Analyst, Data Scientist, Data

Engineer.

What youll need :

BE / B. Tech (Preferred Candidates from Tier I Colleges with Computer Sc.

Engineering)

1-3 years of relevant experience in the Data engineering field

Experience in : Python Coding or Scripting, specifically pandas, numpy, matplotlib,

scipy, and other data wrangling or analysis libraries, Advanced SQL Querying shell

scripting and GIT

Knowledge / hands-on experience of Airflow

Understanding of Data Warehouse concepts and hands on experience in sql query

tuning

Relevant working knowledge on DBs like : Rdbms : Postgresql (Preferred) / Mysql / MS

sql server Nosql : ElasticSearch (Preferred) / MongoDB / Cassandra Data Warehouse :

Amazon Redshift(Preferred), BigQuery Other DBs / storages : Firebase, GCS, S3

Knowledge of redshift administration skills

Experience in cloud platform(s) (preferably aws)

Experience in Devops / ML-ops environment is a plus

Knowledge of FMCG Industry will be an add on

What youll do :

Create and maintain optimal and resilient data pipeline architecture for greater

scalability

Build the infrastructure required for optimal extraction, transformation, and loading of

data from a wide variety of data sources

Expected to spend most of the time with Advanced SQL, Python and other

technologies for data cleaning, wrangling, munging, etc with an open mind to learn

any new technologies

Own the design, development, and maintenance of on-going / new projects, metrics,

and analysis

Can design dashboards to drive key business decisions

Can model datasets and can partner with leaders to answer key business questions

Should be analytical, creative, and quick to absorb business knowledge

Work closely with other teams on topics related to data requirements, cleanliness,

accuracy etc

Work with analytics and data scientist team members to assist them in productionizing

their ML models or other production codes