Senior Data Engineer

- Experience with cloud infrastructure and infrastructure as code; comfortable working with containers, Kubernetes, CI/CD, access controls, and production observability - A track record of leading ambiguous infrastructure initiatives: setting technical direction, making pragmatic architecture tradeoffs, and driving adoption across teams - Experience with event-driven or streaming data infrastructure, including a message broker or managed event bus and a stream processing system - Strong software engineering skills in Python and experience building and operating production data or distributed systems - Sound understanding of CDC, delivery guarantees, idempotency, ordering, schema evolution, and recovery or replay in production pipelines - Deep hands-on Airflow experience beyond writing DAGs: scheduling and execution behavior, deployment, scaling, upgrades, monitoring, and debugging failures - Clear communication and a track record of partnering across teams while owning systems through production support - GCP services such as Pub/Sub, Dataflow, Datastream, BigQuery, GKE, and Cloud Storage - Astronomer, Apache Beam, Terraform, Spacelift, Datadog, dbt, Spark or Dataproc - Supporting both batch and low-latency consumers, including product-facing data services or ML features - Experience supporting ML or AI workloads such as inference pipelines, reproducible evaluations, or governed data access

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