Data Engineer GCP (Google Cloud Plataform)

Job Description

We are looking for a skilled Data Engineer to join our team. As a Data Engineer, you will be

responsible for understanding business and technological challenges, develop data pipelines

tackling those challenges, and ensuring their smooth deployment. You will as well be

responsible of the applications of standard industry and within-the-company good practices,

and the application and evolution of our various patterns. This is a remote position.

MAIN RESPONSABILITIES

• Projects understanding and Communication

o Understand problems from a user perspective and communicate to clearly

understand the issue.

o Ensure the architecture provided by the Data Architect is clearly understood by

yourself.

o Communicate with the Data Architect and your peers on the technical solution

you’re developing and communicate with the Project Manager in charge of the

project you’re working on.

o Write and communicate on new or updated interface contracts.

o Develop data pipelines based on the defined architecture.

o Ensure the regular good practices are applied.

o Deploy requested infrastructure, particularly using Terraform.

o Make peer reviews and ask to your peers to review your code when merging a

new version of the codebase.

o Define tests with your project manager, based on the functional and technical

requirements of the pipeline you’re developing.

o Perform those tests and communicate regularly on the results.

o Regularly summarize the results of your tests in a dedicated document.

o Present to the Data Architect in charge of the architecture, and the Lead

DataOps, the development that was performed through our Deployment

Reviews.

o Track and communicate on any potential errors in the entire period of active

monitoring following a deployment.

o Ensure diligent application of deployment process, logging, and monitoring

strategy.

REQUESTED HARD SKILLS

and at least one year of experience with GCP.

experience with Google Composer is a plus.

optimize tables and queries, and able to design database architecture. The

candidate should know more than the regular creation of tables, and should be

aware of trade-offs in developing and deploying some infrastructure versus others.

pipelines are slowly being rewritten using pySpark, the Data Engineer should be

able to maintain get them evolving.

o Pub / Sub

o Kafka

o Google Cloud Storage

o Dataflow (or Apache Beam)