Data Engineer - Ciudad de México - Sngular

Sngular

Empresa verificada

Ciudad de México

hace 4 semanas

Publicado por:

Rodrigo Fernández

Reclutador de talento para beBee

Descripción

Why join?

People first:
Sngular is a collaborative people-oriented company, where YOU and your perspective will always be valued.

Our number one value is "People before results" and we have created a big family in which each member is taken care of.

You will also have flexible schedules, home office possibilities, digital disconnection, mentoring, days off, and very fun events :
)

Continuous growth and training:

We have a Start-up spirit with the infrastructure of a big organization (we are 1400 already), you will be offered professional growth opportunities, learn new skills, gain new certifications, become a Lead or Manager leave your comfort zone the way YOU want it Your career path and treatment will always be
personalized, tell us what your goal is so we can reach it together.

You will have Internal training, an Annual training allowance, Free unlimited access to
Udemy; Bonus for Obtaining Certifications, Tech talks + Language training.

What will you do:

Design and implementation of Python code and frameworks as a Django.
Working in Azure Cloud with Azure Data Factory.
Build pipelines to enable features to be provisioned for models served by Microservices.
Familiar with data science model building concepts as well as consuming and from data lake.

What you will need to succeed in this role:

At least 5 years of experience working on Python
At least 3 years of experience working with unstructured datasets using PySpark on Spark on Databricks
At least 3 year of experience in cloud technologies: Azure, Docker, Ansible, or Terraform
At least 3 years of experience developing microservices: Python, PySpark, TwistedPy, Django
At least 1 year of experience with a streaming data platform consumption using streaming
At least 1 year of experience with Azure Data Factory.
At least 1 year of experience building data pipelines, CI/CD pipelines, and fit for purpose data stores.