About the client:

The client has a chat-based shopping agent built exclusively for fashion. Designed to redefine how people search and discover fashion, and offers a personalised, conversational experience powered by advanced AI and natural language understanding.

About the role:
As a Data Engineer you will be a foundational member of the team, responsible for designing and building the entire data ecosystem that fuels our AI Personal Stylist. This is a unique opportunity to solve complex technical challenges while directly shaping a product that will revolutionise how people shop online.

Responsibilities:

• Design, build, and optimize scalable, parallel data processing pipelines on Google Cloud to handle massive volumes of offline data.
• Implement and manage large-scale LLM batch inference jobs, processing millions of data points to enrich our product catalog with sophisticated, AI-generated attributes.
• Architect and own the data infrastructure for our Fashion Knowledge Graph, leveraging BigQuery and parallel data processing frameworks
• Develop and maintain robust feature generation pipelines to craft high-quality signals for both the training and inference of our machine learning models.
• Orchestrate complex workflows of data processing jobs, implementing robust monitoring, alerting, and data quality validation systems to ensure reliability and trust in our data.
• Collaborate closely with data science and machine learning teams to understand data requirements and deliver production-grade data solutions.
• Champion engineering best practices, including writing clean, maintainable Python and SQL, and drive a culture of high-quality data and operational excellence.

Required Skills & Experience:

• Data engineering background with strong generalist skills, comfortable with writing code with AI (while still owning it) in various programming languages
• Handling large volumes of data at scale, data warehousing/data lakes. Apache Spark, Polars, Snowflake, etc
• Hands-on experience with workflow orchestration tools like Airflow, Argo, Azkaban or Kubeflow.
• Great understanding of SQL
• Comfortable with CI/CD, testing
• Understands general theoretical complexity (Big O notation)
• Deep understanding of the web stack, useful for scraping, owning problems across the stack
• Great understanding of AI stack - what is possible, what is not, what is expensive
• High autonomy, comfortable with rapidly shifting priorities in a start-up environment

Nice to have experience:

• GO / Java experience
• Scrapy Experience
• Elasticsearch experience (or more generally custom search engine experience)
• Data-science background - ML experiments, feature extraction, etc
• Google Cloud experience

Additional information:

- Work with some of the most dynamic US tech companies, building and iterating on new features and platforms.

- Long-term projects with real technical challenges.

- Fully remote work with flexible hours.

- Collaboration flexibility: We work with B2B (PFA/SRL) contracts.

- 30 paid days off per year.

- We provide equipment as needed (laptop, desktop, etc.).

- Continuous learning: We sponsor career-improving courses, seminars, and certifications.

- Opportunity for annual business visits to the US, depending on project needs.

Get picky and choose a career that matches your mindset and lifestyle. Team up with a company that encourages you to do more and gives you the flexibility you need!