Staff Data Engineer - Sponsored Content & Products (all genders)

Our mission is to digitize the classic shopping stroll, turning it into a personalized, inspiring experience for every customer. Technology and data sit at the center of everything we build. We are not a fashion company with a tech team on the side. Tech drives our product, our strategy, and our growth.
Our proprietary tech stack powers our own shops and SCAYLE, our commerce infrastructure solution that serves over 350 brands globally. Same foundation, bigger stage. The challenges keep things interesting.

The Sponsored Content & Products team is a key growth driver. Its mission is to build highly scalable self-serve cost-per-click (CPC) bidding marketplaces that empower brands to efficiently boost their visibility in real time right at the digital point of sale.

While operating within an existing ecosystem, the architectural transition from a single monolith into four specialized product teams provides a highly autonomous, greenfield-like environment where your design decisions will directly shape our future state and enable us to multiply our Retail Media revenue.

• Bridge Platform & Application Layers: Design, build and maintain high-throughput Reverse ETL replication pipelinesthat bridge the gap between central core platform systems and client-facing reporting tools
• Evaluate Storage & Data Modeling: Actively evaluate whether data is structured correctly for their downstream use cases. Command strategic technical decisions on whether workloads belong in relational engines (MySQL aggregates), fast search indexing layouts (OpenSearch), cloud warehouses (BigQuery), or columnar storage (ClickHouse)
• Pipeline Modernization: Take lead in the migration of our current custom data processing pipelines into a modern, scalable data architecture through a secure transition path
• Cross-Functional Information Architecture: Partner closely with Backend Engineers and Analytics Engineers to map out highly performant, scalable data structures, taking ownership over physical and logical modeling boundaries
• Drive Operational Excellence: Promote operational excellence across our data infrastructure by prioritizing proactive monitoring, system reliability, and overall application health just as much as building new pipelines
• Balance Innovation with Stability: Cultivate a very high standard of data infrastructure health, ensuring that long-term maintainability is valued equally with delivering new features
• Set engineering standards, evaluate technical trade-offs

• 5+ years of professional experience in data platform engineering
• 7+ years of total professional experience in (general) engineering
• Programming Languages: Strong proficiency in Python for writing custom data loading logic, data validation drivers, and cluster-executed sync utilities
• Batch Workflow Orchestration: Expert experience building automated, event-driven batch architectures.. Skilled in configuring state tracking, asset sensors, and task dependency graphs for complex pipeline schedules
• Database Architecture: Advanced understanding of relational and analytical database engines. Expert knowledge of when to leverage transactional relational setups (MySQL transaction isolation levels, query performance tuning) versus highly optimized columnar/document architectures (ClickHouse, OpenSearch, BigQuery)
• Observability & Telemetry: Experience tracking system resources, logging pipeline runtimes, and setting up centralized data alerts within monitoring platforms like Datadog
• Pragmatic & Solution-Oriented Mindset: A practical problem solver who values executing secure, stable transition steps over premature optimization or over-engineering
• Effective Communicator: Able to convey complex architectural concepts, technical designs and performance trade-offs clearly and simply
• High Autonomy & Proactive Ownership: Motivated to work independently, take charge of data initiatives
• Collaborative: Capable of working productively alongside central infrastructure teams to align on data handoffs, platform boundaries and information architecture

Nice to have

• Modern data orchestrators: Experience with modern data orchestrators like Dagster or similar tools
• Data Transformation: Working knowledge of dbt to effectively collaborate and support analytics engineers
• Domain Expertise: Prior experience working within an e-commerce, retail tech, or ad-tech ecosystem, with a solid understanding of commercial retail workflows or funnel metrics
• Practical familiarity or comfort reading object-oriented PHP and frameworks like Laravel is a highly valued bonus, as our existing legacy pipeline and custom orchestrator live natively inside this environment