Senior Backend Engineer, Data Product

Candidates should have 5+ years of backend engineering experience with deep expertise in designing and scaling backend systems for data-rich applications. Strong Python development skills are required, with bonus points for experience in Go or other typed backend languages. The role demands experience designing and maintaining robust APIs, including schema design, versioning, and system observability. Expertise in distributed data systems such as Spark, Kafka, Flink, or Dataflow for large-scale data ingestion and transformation is essential. Familiarity with data stores like BigQuery and Postgres, including performance tuning for large, complex queries, is necessary. Production experience with workflow orchestration tools like Airflow or dbt, and containerized deployment (Docker, Kubernetes) is expected. Understanding of cloud infrastructure (e.g., GCP, AWS), including CI/CD pipelines, Terraform-based deployments, and observability with tools like Datadog or Prometheus, is required. Demonstrated success building high-impact backend systems that shipped to production and scaled with user or data growth is a must.