The Data Engineer that will fit should have 4 years of hands on experience in such a role, most of which in a
e-commerce companies. It is expected that the candidate will have working experience building data pipelines:
ETL/ELT processes, modelling data in dbt to clean and process it, connecting to APIs to pull and
push data to peripheral applications, working with python, automating/optimising data infrastructures.
The engineer will work as part of a team of 6: senior and junior data engineers, and analysts.
The infrastructure is built on Google Cloud Platform: where Python is of core use, data streaming, Google BigQuery, dbt, Prefect and Tableau. Purpose is to introduce AI features and predictive functionality in this environment.
Preferably the engineer will have common know-how use of Linux environment
Tasks:
● Design, develop, and maintain scalable data pipelines, ETL processes, and data integration
workflows using Google BigQuery, dbt, Prefect, and Tableau
● Create and implement data models and machine learning algorithms for efficient data
transformation
● Identify and troubleshoot data-related issues, proposing and implementing effective
solutions
● Connect to peripheral applications: Exponea/Bloomreach, Salesforce, Odoo, Magento to
send and receive data.
Requirements:
● Minimum of 4 years of experience as data engineer, handling e-commerce data projects
and building data pipelines.
● Minimum a Bachelor's degree, ideally in Engineering or Science.
● Strong proficiency in Python and SQL.
● Proven experience in building ETL/ELT processes.
● Proven experience with data modelling, ideally in dbt.
● Proven experience with Google BigQuery.
● Ability to understand the broader technical infrastructure and the role of the data
platform within it.
● Familiarity with Bloomreach Exponea, Salesforce, Tableau, Magento, and Odoo will be
advantageous!