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Data Analytics Engineer

extra holidays - fully flexible

Remote:

Hybrid

Contract:

Full time

Work from:

Porto (PT)

Offer summary

Qualifications:

Strong Python programming skills., Proficient in SQL and data pipeline frameworks., Experience with ETL processes and big data technologies., Understanding of statistical concepts relevant to experimentation..

Key responsabilities:

Enhance in-house experimentation platform.
Support large-scale statistical tests.

Farfetch Large http://www.farfetch.com

1001 - 5000 Employees

See more Farfetch offers

Job description

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.

PORTO

Our Porto office is located in Portugal's vibrant second city, known for its history and its creative yet cosy environment. From Account Management to Technology and Product, whatever your skills are, you'll find your fit here.

THE ROLE

We seek an experienced and innovative Analytics Engineer to join our Data Analytics & Experimentation team at Farfetch. This role will focus on the evolution of our award-winning in-house experimentation platform, with a special emphasis on advancing our custom statistical engine that processes test results and enables self-service, automated analytics for teams across the company. This is a unique opportunity to contribute to a cutting-edge platform that drives critical insights for one of the world’s largest luxury fashion platforms. As a Data Analytics Engineer, you will collaborate with data analysts, data engineers, and product managers to optimise our experimentation and Data infrastructure, ensuring robustness, scalability, and flexibility to meet the analytical needs of Farfetch teams globally.

WHAT YOU'LL DO

Experimentation Platform Development: Work closely with cross-functional teams to continuously enhance our in-house experimentation platform, including building and refining features within our custom statistical engine.

Statistical Processing: Support and enhance the platform's ability to process large-scale statistical tests, including A/B and multivariate tests, with a focus on delivering accurate, actionable insights across teams.

Data Engineering: Design and implement efficient, scalable data pipelines and ETL processes for experimentation data, ensuring reliable data flow from ingestion through to final analysis.

Self-Service Analytics: Develop self-service capabilities, enabling non-technical users to perform automated deep dives and access critical insights independently.

Quality and Testing: Implement robust testing frameworks to ensure the accuracy and reliability of experimentation results, and automate quality checks for all analytical outputs.

Documentation and Training: Create clear documentation for new features, processes, and tools, and provide training sessions to educate end-users on best practices in experimentation and data analysis.

WHO YOU ARE

Python Development: you have strong Python programming skills, with experience in libraries commonly used in data engineering and statistical analysis (e.g., pandas, NumPy, SciPy).

Data Engineering Expertise: proficient in SQL and experienced in data pipeline frameworks (e.g., Airflow, dbt), ETL processes, and big data technologies (e.g., Spark).

Analytical Mindset: able to understand statistical concepts relevant to experimentation (e.g., confidence intervals, p-values, hypothesis testing) and forecasting models with the capability to implement these concepts programmatically.

Data Modelling: you develop and maintain robust, scalable, and efficient data models that support business intelligence, analytics, and operational workflows, ensuring alignment with business requirements and industry best practices.

Collaboration & Communication: you have strong interpersonal and communication skills to work effectively across teams and support both technical and non-technical users.

As a Data Analytics Engineer, you will collaborate with data analysts, data engineers, and product managers to optimise our experimentation and Data infrastructure, ensuring robustness, scalability, and flexibility to meet the analytical needs of Farfetch teams globally.