F

Data Analyst

icon building Empresa : Farfetch
icon briefcase Tipo de Emprego : Periodo Integral

Número de Aplicantes

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000+

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Descrição do Emprego - Data Analyst

Farfetch is a leading global marketplace for the luxury fashion industry, connecting customers in over 190 countries with items from more than 50 countries and over 1,400 of the world’s best brands and charming boutiques from around the world. Farfetch opens a world of luxury for endless expressions of style, delivering a truly unique shopping experience and access to the most extensive selection of luxury on a global marketplace.

 

OPERATIONS

The Operations team serves as the backbone of our marketplace, seamlessly managing the entire order journey. From creating online content and ensuring secure payments to order fulfillment and delivery, while providing comprehensive customer and partner care, this team is relentlessly focused on improving the customer experience every single day.

 

PORTO
Our office is near Porto, in the north of Portugal, and is located in a vibrant business hub. It offers a dynamic and welcoming environment where our employees can connect and network with a large community of tech professionals.
 

THE ROLE


We are looking for a highly analytical and business-oriented Data Analyst to join our Data Analytics, Automation & AI team. In this role, you will transform complex datasets into actionable insights, build scalable analytics solutions and contribute to AI-enabled initiatives that support strategic and tactical decision-making.


The ideal candidate has strong expertise in Python, modern analytics practices and hands-on experience with Google Cloud Platform (GCP) data products. The candidate should be comfortable working with large datasets, designing reporting frameworks, automating workflows and communicating insights to both technical and non-technical audiences.



Key Responsibilities




  • Analyze large and complex datasets to identify trends, opportunities and business insights using Google BigQuery;




  • Develop scalable data pipelines, automated reporting solutions and analytical models using Python and Airflow;




  • Work with GCP services, primarily BigQuery and Looker, to build and optimize analytics workflows;




  • Design and maintain dashboards, KPIs and self-service reporting solutions for business stakeholders;




  • Translate business requirements into analytical solutions and actionable recommendations;




  • Collaborate with engineering, product and operations teams to support data-driven decision-making;




  • Perform data validation, quality checks and root-cause analysis to ensure data integrity;




  • Optimize SQL queries and improve performance of large-scale data transformations;




  • Support automation and AI-driven initiatives by leveraging modern analytics and data engineering practices;




  • Document analytical processes, data models and reporting frameworks to ensure maintainability and scalability.




Required Qualifications




  • Bachelor’s degree in Data Analytics, Computer Science, Statistics, Mathematics, Engineering or a related field;




  • 3+ years of experience in data analytics, business intelligence or analytics engineering roles;




  • Advanced proficiency in Python for data analysis, automation and workflow development;




  • Strong SQL skills and experience working with large-scale relational and analytical databases;




  • Hands-on experience with Google Cloud Platform (GCP), particularly BigQuery and Looker;




  • Strong understanding of data modeling, ETL/ELT processes and analytics engineering concepts;




  • Experience working with orchestration and automation tools such as Airflow;




  • Experience working with version control systems such as Git;




  • Excellent communication and stakeholder management skills, with the ability to present insights to technical and non-technical audiences;




  • English proficiency is mandatory;




  • Curious mindset, proactive attitude and strong collaboration skills.




Preferred / Nice to Have Qualifications




  • Exposure to Data Science and Machine Learning concepts, including predictive modeling and statistical analysis;




  • Familiarity with modern AI such as Natural Language Processing (NLP), Large Language Models (LLMs) and deep learning frameworks;




  • Knowledge of machine learning libraries and frameworks such as Scikit-learn, TensorFlow or PyTorch;




  • Experience working in Agile environments and using tools such as Jira and Confluence.




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;

  • Flexible benefits program.

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. 


SCAM DISCLAIMER



  • It has come to our attention that there may be fraudulent activities involving individuals or organizations falsely claiming to represent Farfetch in order to attract candidates to a SCAM. Please be aware that Farfetch does not conduct recruitment processes through messaging apps or any unofficial communication channels, other than our official careers website. Additionally, Farfetch will never ask candidates for any form of payment during the recruitment process.


We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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