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GFG - Data Engineer

Global Fashion Group (“GFG”) is the #1 online fashion platform for emerging markets. It operates across four continents and 25 countries and employs over 9,000 people via its five brands / ventures: ZALORA in Southeast Asia, THE ICONIC in Australia and New Zealand,NAMSHI in Middle-East, DAFITI in Brazil/Latam and LAMODA in Russia/Ukraine/Kazakhstan/Belarus.

At GFG, Technology is core to long-term success and is a crucial enabler of a great Customer Experience. We’re 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 and the ventures.

If this sounds like your kind of gig, be part of a creative, passionate and dynamic team that works hard but throws a great party as well!

We are looking for a Data Engineer happy to build, maintain and automate big data environments (datalake, etc…) and the associated data to enable the teams to make use of the high volume of data available from our e-commerce activities.

You should be proficient in:

Technical background:

  • Languages such as Python, Scala and eventually Golang
  • Use of Big Data technologies (Hadoop, Spark, Elastic Stack…), of SQL and NoSQL databases
  • Experience in cloud environment (AWS) is a plus

Data management: you have experience in integrating / managing large volumes of Data while taking into account performance issues and in handling data quality (cleaning, data mapping / transformation, standardization…)

Engineering skills: experience of working with github, jenkins with strong coding practices on how to optimize data manipulation on big volume

You should have the following qualifications:

  • BS in Computer Science or related technical discipline or equivalent practical experience
  • 3-4+ years of experience with high-traffic, high volume, high scalable distributed systems and client-server architectures
  • Some experience working with Data Scientists and finding solutions for them to work efficiently while manipulating high volume of data and be able to work with them and the teams to bring their algorithms at scale
  • Operational experience with AWS, container approaches...
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