• Bachelor's degree (or equivalent) in Computer Science or a related field.
• 5+ years of experience building distributed system architecture, from whiteboard to production.
• Strong programming skills in Python, and SQL or SparkSQL.
• Versatility. Experience across the entire spectrum of data engineering, including:
• Data stores (e.g., ClickHouse, ElasticSearch, Postgres, Redis, and Neo4j)
• Data pipeline and workflow orchestration tools (e.g., Airflow, DBT, Luigi, Azkaban, Storm)
• Data processing technologies and streaming workflows (e.g., Spark, Kafka, Flink)
• Deployment and monitoring infrastructure in public cloud platforms (e.g., Docker, Terraform, Kubernetes, Datadog)
• Loading, querying, and transforming large data sets
• AI-native mindset: ability to leverage modern AI/ML tools and workflows to accelerate engineering productivity, data processing, and problem solving