Lyst are looking for a Data Engineer to join our Analytics team and
work on the huge data projects that are integral to Lyst’s day to day
operations.
Data lies at the heart of everything we do here at Lyst, from
understanding our users better to making mission critical decisions.
We record nearly 100 million rows of data a day just from user
interactions. To support this volume, we have built our own analytics
architecture, predominantly in Python and leveraging the convenience of
many cloud services like AWS Redshift, Lambda, CloudFront, S3.
You will work hand in hand with our analysts and data product
managers to ensure that our analytics data pipeline is scalable, stable
and secure as the business and traffic increases. From re-architecting
the pipeline, to building bespoke BI tools you will work on things such
as:
Improving our analytics data architecture, ensuring scalability and resilience for all ETL processes.
Streamlining the anomaly detection process across all our data,
building tools and processes around it to speed up the required actions
to solve any anomalies.
Improving our internal BI tool, Looker, and tools surrounding it to
ensure Analysts are able to provide amazing insight to the business.
Understanding the query requirements from our data analysts and
optimising our database (table) design to make them faster and more
efficient.
Fixing the interesting problems we face in the best way possible; as
we are not constricted to tool sets and languages, if you find a
solution to a problem that will work better, we'll use your idea. Best
idea wins.
Creating a development platform, tools and pipeline that is effective and easy to iterate with.
You'll be comfortable using all of the following:
Python, JavaScript, Django, PostgreSQL, Redis, AWS, Objective-C,
Elasticsearch, Docker, Ember.js, RedShift, Pandas, IPython Notebook.
