Mô tả công việc
is the leading fashion and lifestyle destination in growth markets across LATAM, SEA and ANZ. From our people to our customers and partners, we exist to empower everyone to express their true selves through fashion. Our three e- commerce platforms: Dafiti, ZALORA and THE ICONIC connect an assortment of international, local and own brands to over 800 million consumers from diverse cultures and lifestyles. GFG’s platforms provide seamless and inspiring customer experiences from discovery to delivery, powered by art & science that is infused with unparalleled local knowledge. As part of the Group’s vision is to be the 1 online destination for fashion & lifestyle in growth markets, we are committed to doing this responsibly by being people and planet positive across everything we do.
ABOUT THE TEAM
Our vision to bring affordable and sustainable fashion to customers in our markets is powered by technology and data. The GFG Data Team is an integral part of GFG and is essential to enabling a data- driven decision- making culture.
ABOUT THE ROLE
As the Lead Data Engineer in the Data team, you will be working on all aspects of Data, from Platform and Infra build out to pipeline engineering and writing tooling/services for augmenting and fronting the core platform. You will be responsible for building and maintaining the state- of- the- art data Life Cycle management platform, including acquisition, storage, processing and consumption channels. The team works closely with Data Scientists, Data Analytics, Business Intelligence and business stakeholders across the GFG in understanding and tailoring the offerings to their needs.
THE IMPACT YOU’LL MAKE
Build and manage a highly scalable, efficient Data and ML Infrastructure by adopting microservices driven design and architecture with proper DevOps principles and practices
Help the team in integrating various data sources across GFGs group vertical
Build and expose metadata catalog for the Data Lake for easy exploration, profiling as well as lineage requirements
Build and manage the data asset using some of the most scalable and resilient open source big data technologies like Airflow, Spark, Kafka, etc
Design and deliver the next- gen data lifecycle management suite of tools/frameworks, including ingestion and consumption on the top of the data lake to support real- time as well as batch use cases
