Impress employers and recruiters.
Choose from hundreds of resume examples.

Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

Design, build, and operate data systems for Decagon's AI products, owning critical data pipelines and storage layers end-to-end, improving reliability and performance, and enabling confident data work at scale for all engineers.

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 tools like Kafka, Flink, and Airflow.
• Own our analytical data layer, including 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/partitioning, and hitting tight p95/p99 targets.
• Lead infrastructure-as-code (Terraform) and GitOps practices for data systems, reducing 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: 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 skills (OpenTelemetry, Prometheus/Grafana, Datadog) and strong incident response discipline.
• Clear written communication and the ability to translate ambiguous data requirements into simple, reliable designs.
• 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.

Skills

• Kafka
• Flink
• Airflow
• ClickHouse
• BigQuery
• Terraform
• GitOps
• OpenTelemetry
• Prometheus
• Grafana
• Datadog
• Debezium
• Dagster
• Prefect
• Spark
• Dask
• Snowflake
• Redshift
• Databricks
• Kubernetes
• GKE
• EKS
• AKS
• GCP
• AWS
• Azure
• dbt
• MSK
• Pub-Sub
• RabbitMQ
• Data pipeline design
• Streaming systems
• Batch ingestion
• Analytical data layer management
• Schema design
• Query performance optimization
• Cost optimization
• Data solution architecture
• Performance evaluation
• Feature scaling
• Pipeline latency tuning
• Query latency tuning
• Caching
• Partitioning
• On-call participation
• Automation
• Incident response
• Written communication
• Data infrastructure operation
• High availability
• Low latency
• Observability
• CDC tooling
• Orchestration frameworks
• Large-scale data processing
• Cloud data warehouses
• Multi-cloud exposure
• Customer-managed deployments

Location

• In-office
• United States

Work Type

• In-office
• Full-time

Experience Level

• Senior
• 5+ years of experience

Salary/Compensations

• $200K - $400K
• Competitive equity

Benefits

• Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave).
• Medical, Dental, and Vision benefits for you and your family.
• Life Insurance and Disability Benefits.
• Retirement Plan (e.g., 401K, pension).
• Parental Leave.
• Fertility and family building benefits through Carrot.
• Daily lunches and snacks in the office.

About the Company

• Decagon is a leading conversational AI platform empowering brands to deliver concierge customer experiences.
• Its technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents for personalized interactions across voice, chat, email, SMS, and other channels.
• The company is building a future where customer experiences are redefined for faster resolutions, richer conversations, and deeper relationships.
• Backed by world-class investors including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures.
• An in-office company driven by excellence and velocity, with values: Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle.
• The Infrastructure team builds and operates Decagon's foundations: networking, data, ML serving, developer platform, and real-time voice.
• The team partners with product, data, and ML to deliver high-scale, low-latency systems with clear SLOs and strong developer ergonomics.
• Focus areas include Core Infra (foundational cloud stack), Data Infra (streaming/batch data platforms), ML Infra (GPU and model-serving platforms), and Platform (DevEx: CI/CD, paved paths, core services).
• The mission is to deliver magical support experiences with AI agents working alongside humans to resolve issues quickly and accurately.