Data Engineer

• Architect the entire data platform from scratch — including event capture, batch and streaming pipelines, and feature engineering
• Build and scale ETL from raw app events to ML-ready features
• Build real-time and batch pipelines for user actions and events
• Contribute to the feature store, embedding pipelines, data validation, and freshness monitoring systems
• Design data layers for use in A/B tests, product metrics, and ML training
• Partner with ML engineers to deliver data adapters for model inputs, embedding generation, and training loops
• Help evolve the core event schema and data model with privacy, observability, and performance in mind

Ideal Profile

• You’re a systems thinker who starts with data and designs for scale. You’ve likely exposure at early-stage or high-scale consumer platforms — social, gaming, transactions, or media.
• 4–8 years of building scalable data systems in fast-moving environments
• Experience supporting RecSys, ML, or content feeds in social or consumer platforms
• Understands how features feed into models, or has worked closely with ML teams before
• Understands how data impacts user experience, not just analytics
• Kafka, Spark, Flink, Airflow, dbt, Redis, BigQuery, Feast, Terraform, Pick your best tool for the job

Nice to Haves

• Experience with personalisation systems, recommender pipelines, or ranking models
• Exposure to A/B testing platforms or online experimentation infrastructure
• Passion for consumer social or dating products

Why Join Us Now

• Join a founding data team where your work is core to the product experience
• Shape key decisions for a platform that will directly impact how people form meaningful relationships
• Significant ESOPs and wealth creation with market-competitive cash compensation