Job description: 

GCP requirements:

• Familiar with Vertex AI pipeline/kubeflow pipelines
• Familiar with BigQuery,
• can code SQL
• Familiar with Cloud composer / airflow
• Familiar with IAM, service account
• Familiar with Data catalog
• Understand Infrastructure as Code
• Good to have knowledge with Dataflow, and K8s.

Cloud agnostic skills

Python:

Deep knowledge about python programing, practice OOP, following coding best practice, know how to use flake8, mypy, black, SonarQube and pre-commitDeep knowledge in unit test and end to end test, familiar with Pytest, fixtures, unittest etc 

Unix:

Familiar with popular Unix system, know how to install sth in docker.Familiar with shell

Git:

Know how to create PR and solve merge conflict.Can create CI/CD pipeline in either Github Action using best practice 

Docker:

Deep understanding with Docker 

DBT:

Deep Knowledge in DBT, preferably with GCP 

SQL

Deep knowledge of SQL 

Deep understanding with Data modeling, system design 

Soft skills:

• Can do attitude,
• Problem solving, even if there is sth new that you don't know. You have a proper way to solve it. For example, knowing how to Google is always good.
• Communication skills with Stakeholders and tech ppl.
• Love code review and feedback
  

This role is in a team that works with customer-facing recommendation systems, so previous experience with high-availability APIs, machine learning–based recommendation, and personalization systems is considered a merit. 

Required cloud certification: Professional Machine Learning Engineers