Assemble large, complex data that meet functional/non-functional business requirements
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing transformation for greater scalability, etc
Use the infrastructure/services required for optimal extraction, transformation, and loading of data from a wide variety of data sources using GCP services
Work with stakeholders including the Product, Data and Design teams to assist with data-related technical issues and support their data requirement needs
Requirement
Bachelor's degree with Minimum 1.5+ years of experience working in globally distributed teams successfully
Must have experience working on Python and data handling frameworks(spark, beam, etc)
Apply experience with cloud storage and computing for data pipelines in GCP (GCS, BQ, composer, etc)
Write pipelines in Airflow to orchestrate data pipelines
Experience handling data from 3rd party providers is a great plus: Google Analytics, Google Ads etc.
Experience in manipulating, processing and extracting value from large disconnected data sets.
Experience with software engineering practices in data engineering, e.g. release management, testing, etc and corresponding tooling (dbt, great expectations)
Basic knowledge on dbt is a good to have
Knowledge on data privacy and security
Excellent verbal and written communication skills
Perks:
Monthly long weekends every third Friday off
Wellness reimbursement to support your health and balance
Paid parental leave
Remote-first with flexibility and trustWork with a world-class data and marketing team inside a globally recognized brand