Decagon offers a collaborative, data-driven culture in San Francisco with an onsite work setup. This role comes with a competitive salary range of USD 200,000 to 400,000 per year, equity, comprehensive medical, dental, and vision benefits, life and disability coverage, retirement plans, parental leave, fertility and family-building support, and daily lunches in the office. The Senior Data Infrastructure Engineer will own end-to-end data pipelines and storage for the AI products, improving reliability and performance while enabling engineers to work with data at scale.
Responsibilities
- 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 Kafka, Flink, and Airflow.
- Own the 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 by optimizing data paths, applying smart caching and partitioning, and targeting p95/p99 performance.
- 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.
Requirements
- 5+ years building and operating production data infrastructure at scale.
- Hands-on experience with Tier 1 data technologies such as ClickHouse, Kafka (or MSK / Pub/Sub / RabbitMQ), and Flink or dbt.
- Proven track record delivering high availability and low latency across streaming and batch workloads.
- Strong observability capabilities (OpenTelemetry, Prometheus/Grafana, Datadog) and solid incident response discipline.
- Clear written communication and the ability to translate ambiguous data requirements into simple, reliable designs.
Technologies
- Kafka, MSK, Pub/Sub, RabbitMQ
- Flink, Airflow, dbt
- ClickHouse, BigQuery
- Terraform, Kubernetes, GKE, EKS, AKS
- Snowflake, Redshift, Databricks
- Debezium, Dagster, Prefect, Spark, Dask
- OpenTelemetry, Prometheus, Grafana, Datadog
- GCP, AWS, Azure
Compensation
Salary range: USD 200,000 - 400,000 per year, plus equity. Compensation is determined by experience, skills, and scope of responsibilities, with flexibility for exceptional impact.
Benefits
- Take what you need vacation policy (local requirements apply; UK employees receive 25 days of statutory leave)
- Medical, Dental, and Vision coverage for you and your family
- Life Insurance and Disability Benefits
- Retirement Plan
- Parental Leave
- Fertility and family-building benefits through Carrot
- Daily lunches and snacks in the office
About the team
The Infrastructure team builds and operates the foundations that power Decagon, including networking, data, ML serving, developer platform, and real-time voice. We collaborate closely with product, data, and ML to deliver high-scale, low-latency systems with clear SLOs and strong developer ergonomics. Focus areas include Core Infra, Data Infra, ML Infra, and Platform (DevEx).
About the role
We are hiring a Senior Data Infrastructure Engineer to design, build, and operate the data systems that power Decagon's AI products. You will own critical data pipelines and storage end-to-end, enhance reliability and performance, and create paved paths that enable every Decagon engineer to work confidently with data at scale. In this role you will design and implement high-throughput data pipelines and streaming systems with strong SLOs, build real-time and batch ingestion infrastructure with Kafka, Flink, and Airflow, own the analytical data layer, partner with teams, tune latency, lead IaC and GitOps, and participate in on-call to reduce toil.
