Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
5+ years of professional experience in backend or data engineering with large-scale distributed systems
Strong experience with Spark, and with a scripting language (Python, Ruby, Bash)
Experience with distributed storage, querying, and streaming technologies (e.g. Clickhouse, Hive, Presto, Delta, Iceberg, Kafka)
Strong SQL skills (MySQL, PostgreSQL or similar), with experience conducting advanced performance tuning and querying high volume events data (e.g. geospatial, behavioural)
Strong data quality instincts, with hands-on experience using tools like dbt, Great Expectations, or Monte Carlo to diagnose and resolve issues in complex datasets
Experience with workflow orchestration (e.g., Airflow, Prefect) and infra tooling (e.g., Terraform, Docker, Kubernetes), preferably in an AWS context
Experience designing API schemas and building backend services in a microservices architecture
Proficient and effective in using AI tools (e.g. Copilot, Claude Code, Cursor) to accelerate coding and engineering workflows
Excellent communication skills, with the ability to articulate technical concepts clearly to both technical and non-technical audiences while collaborating effectively across teams
Bonus: Experience with LLM orchestration or vector databases, or with experimentation/simulation platforms and A/B testing infrastructure at scale