Senior Data Engineer

Global Fashion Group 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 TEAMAt GFG, technology is core to long-term success and is a crucial enabler of a great customer experience. We are a mix of experts in fashion, logistics, data analytics, marketing and design, guided by business consultants and tech geniuses - everyone contributes to the success of GFG. ABOUT THE ROLE
Work daily to scale machine learning problems. For this purpose, you are expected to be involved in the process of collecting, storing, processing, and analyzing data generated from our database, in addition to joining our data scientists in the design of machine learning models.
Work in a diverse, international setting with teammates who are experts in various topics. We often conduct workshops to improve our individual skill sets, and to improve our workflow as a team. The role is based in our Vietnam office.
THE IMPACT YOU'LL MAKE Data at GFG never stops growing and the team also never stops learning, innovating and expanding so that we can bring in or build the latest and best tools and technologies. In this role, you will be able to create strategic data models, develop and maintain data architecture used to power high-impact business initiatives that contribute to the overall growth and strategy for GFG.