Senior Data Infrastructure Engineer

About the Role

We're hiring a Senior Data Infrastructure Engineer to design, build, and operate the data systems that power Decagon's AI products. You'll own critical data pipelines and storage layers end-to-end, improve reliability and performance, and create paved paths that let every Decagon engineer work confidently with data at scale.

In this role, you will

• Design and implement high-throughput data pipelines and streaming systems with strong SLOs, clear runbooks, and actionable telemetry.
• Build and operate real-time and batch ingestion infrastructure using tools like Kafka, Flink, and Airflow.
• Own our analytical data layer — schema design, query performance, and cost optimization across ClickHouse, BigQuery, or similar.
• Partner with research and product teams to architect data solutions, evaluate performance, and scale new features.
• Tune pipeline and query latencies: optimize data paths, apply smart caching/partitioning, and hit tight p95/p99 targets.
• Lead infrastructure-as-code (Terraform) and GitOps practices for data systems; reduce drift with reusable modules and policy-as-code.
• Participate in on-call and drive down toil through automation and elimination of recurring data issues.

Your background looks something like this

• 5+ years building and operating production data infrastructure at scale.
• Hands-on experience with Tier 1 data technologies: ClickHouse, Kafka (or MSK/Pub-Sub/RabbitMQ), and Flink or dbt.
• Proven track record meeting high availability and low latency targets across streaming and batch workloads.
• Excellent observability chops (OpenTelemetry, Prometheus/Grafana, Datadog) and strong incident response discipline.
• Clear written communication and the ability to turn ambiguous data requirements into simple, reliable designs.

Even better if you have

• Experience with CDC tooling (Debezium) and orchestration frameworks (Airflow, Dagster, or Prefect).
• Familiarity with Spark or Dask for large-scale data processing.
• Experience with cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks).
• Experience being an early data/platform/infrastructure engineer at another company.
• Strong Kubernetes experience (GKE/EKS/AKS) and multi-cloud exposure (GCP, AWS, Azure).
• Experience with customer-managed deployments.