Data Engineering Expert for Luxury Fashion Ecosystem
2 semanas atrás
FARFETCH is a global platform for luxury fashion, connecting creators, curators, and consumers. As a Data Analytics Engineer, you will contribute to the evolution of our award-winning in-house experimentation platform.
Key Responsibilities:- Develop and refine features within our custom statistical engine to enhance experimentation capabilities
- Support large-scale statistical tests, including A/B and multivariate tests, to deliver accurate insights across teams
- Design efficient data pipelines and ETL processes for experimentation data, ensuring reliable data flow from ingestion to final analysis
About You:
- Strong Python programming skills with experience in libraries commonly used in data engineering and statistical analysis (e.g., pandas, NumPy, SciPy)
- Data engineering expertise with proficiency in SQL and experience in data pipeline frameworks (e.g., Airflow, dbt), ETL processes, and big data technologies (e.g., Spark)
- Ability to understand statistical concepts relevant to experimentation and implement these concepts programmatically
- Collaboration and communication skills to work effectively across teams and support both technical and non-technical users
Working at FARFETCH:
- The Porto office is located in Portugal's vibrant second city, known for its history and creative yet cosy environment
- A unique opportunity to contribute to a cutting-edge platform that drives critical insights for one of the world's largest luxury fashion platforms
What We Offer:
- An estimated salary of $120,000 - $150,000 per year, depending on your level of experience
- A chance to collaborate with talented individuals who share your passion for data analytics and experimentation
- The freedom to break traditions and revolutionize the industry with innovative solutions
About FARFETCH:
- We exist for the love of fashion and are committed to being a positive platform for good
- We welcome differences, empower individuality, and celebrate diverse skills and perspectives
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