Senior Data Engineer

PT Lisbon

Full Time Senior-level / Expert
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Farfetch
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Posted 2 weeks ago

FARFETCH exists for the love of fashion. Our mission is to be the global platform for luxury fashion, connecting creators, curators and consumers.




We're a positive platform for good, bringing together an incredible creative community made up by our people, our partners and our customers. This community is at the heart of our business success. We welcome differences, empower individuality and celebrate diverse skills and perspectives, creating an inclusive environment for everyone. We are FARFETCH for All.
TECHNOLOGY
We're on a mission to build the technology that powers the global platform for luxury fashion. We operate a modular end-to-end technology platform purpose-built to connect the luxury fashion ecosystem worldwide, addressing complex challenges and enjoying it. We're empowered to break traditions and revolutionise, with the freedom and autonomy to make a difference for our customers all over the world.
LISBON
Our Lisbon office is located in Portugal's cosmopolitan capital. Mostly the teams here are focused around Technology and Store of the Future. In this office, Farfetchers like to have catch ups in the ball pit or creative moments by the grand piano!
THE ROLE
We are looking for a Data Engineer to join our team: we manage end-to-end functionality of large-scale data products, using automation and Machine Learning to improve our Business Platform and with special focus on fraud detection and risk management systems. You will report to the Engineering Manager responsible for this area and will work along with other Data Engineers, Data Scientists and Analysts. You will be part of team that is always on the tip of new technologies, shaping the technical direction of this critically important part of Farfetch. Working with us, you will create and maintain data science solutions to be integrated with the relevant internal business products and operational systems.

WHAT YOU'LL DO

  • Help design the solutions to allow proper training and live serving of Machine Learning Models;
  • Work with technical partners to implement the end-to-end architecture;
  • Build the tools to give more autonomy to Data Scientists in their daily work;
  • Ensure outstanding engineering practices when building this data services (monitoring, alarms, tests and CI/CD);
  • Surface the team's output through the construction of ETLs, APIs and messaging systems;
  • Deal with batch and stream processing of data, with special focus on the later;

WHO YOU ARE

  • Experience implementing end-to-end data products with Data Engineering and Machine Learning components - from the system design to construction, deployment, orchestration and monitoring;
  • Experience writing production quality code in Python or Scala
  • Exposure to data processing frameworks such as Dataflow, Spark, Flink, MLFlow or Databricks is a plus

REWARDS & BENEFITS

  • Health insurance for the whole family, flexible working environment and well-being support and tools
  • Extra days off, sabbatical program and days for you to give back for the community
  • Training opportunities and free access to Udemy
  • Flexible benefits program
  • FARFETCH Equity plan

EQUAL OPPORTUNITIES STATEMENT

  • FARFETCH is an equal opportunities employer ensuring that all applicants are treated equally and fairly throughout our recruitment process. We are determined that no applicant experiences discrimination on the basis of sex, race, ethnicity, religion or belief, disability, age, gender identity, ancestry, sexual orientation, veteran status, marriage and civil partnership, pregnancy and maternity, or any other basis prohibited by applicable law. We continue to build our consciously inclusive culture as part of our Positively FARFETCH strategy throughout our business, partnerships and communities.
As a Data Engineer at Farfetch you will build the foundations on which Machine Learning models will run.
Job tags: Engineering Machine Learning Python Scala Spark
Job region(s): Europe
Job stats:  7  0  0
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