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Senior Data Infrastructure Engineer

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Aircall
Full Time position
Listed on 2026-08-30
Job specializations:
  • IT/Tech
    SRE/Site Reliability, Data Engineering
Salary/Wage Range or Industry Benchmark: 150000 - 200000 USD Yearly USD 150000.00 200000.00 YEAR
Job Description & How to Apply Below

Aircall is a unicorn, AI-powered customer communications platform used by 22,000+ companies worldwide to drive revenue, resolve issues faster, and scale customer‑facing teams. We’re redefining customer communications by bringing voice, SMS, Whats App, and AI together into one seamless workspace.

Our momentum comes from a simple idea: help teams work smarter, not harder. Aircall’s AI Voice Agent automates routine calls, AI Assist streamlines post‑call work, and AI Assist Pro delivers real‑time guidance so people can do their best work. The result is higher revenue, faster resolutions, and teams that scale with confidence.

Aircall is headquartered in Paris, our European HQ, with a strong North American presence anchored in Seattle, our North American HQ, and teams across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City. We’ve built a product customers love and a business that’s scaling quickly, backed by world‑class investors and driven by rapid AI innovation across multiple product lines.

At Aircall, you’ll join a company in motion. We’re ambitious, product‑driven, and execution‑focused, with visible impact, fast decisions, and real growth.

How we work at Aircall

We’re customer‑obsessed, data‑driven, and focused on delivering meaningful outcomes. We value ownership, continuous learning, and thoughtful speed. If you thrive in a collaborative, fast‑moving environment where trust and impact matter, you’ll feel at home here.

About the role

Aircall’s Data team is mid‑migration: we are moving off a single Redshift cluster onto an Apache Iceberg lakehouse on S3, with Flink CDC into Kafka for ingestion and dbt‑on‑Spark via Apache Kyuubi on EKS for transformation. It's a real greenfield platform build — already scoped and underway — on top of a stack that carries ten years of startup‑growth history, and all the quirks that come with it.

We're building this role to give platform work the runway it deserves. Right now, our engineers wear two hats — owning the infrastructure and the business datasets running on top of it — and we're ready to invest in the high‑leverage frameworks that will make both jobs easier: data quality automation, schema registry, and staging and gated promotion. This is a dedicated platform seat: your chance to build those foundations from the ground up.

Your customers are the analytics engineers, data scientists, and AI agents who build on what you ship, and your product is their leverage.

What you will do
  • Build and operate the lakehouse:
    Apache Iceberg on S3, table design and maintenance, partitioning and compaction, and the migration of remaining Redshift workloads onto it
  • Own ingestion end to end — Flink CDC → Kafka (MSK) → Iceberg, plus Rudderstack, Fivetran and DMS sources — and hold the freshness and reliability SLAs on it
  • Run and evolve the compute and orchestration layer:
    Apache Kyuubi on EKS for dbt-spark, Airflow (completing its ECS → EKS migration), autoscaling, spot strategy and cost efficiency
  • Build the tooling, libraries and templates that let analytics engineers and data scientists own their own pipelines without filing a ticket — self‑service is the deliverable, not a side effect
  • Close our environment gaps: a real staging environment, CI that tests against staging rather than production, automated schema‑change detection, gated promotion and canary deploys for critical models
  • Own governance and access at the platform level:
    Lake Formation row/column RBAC, StrongDM zero‑trust access, SSO, audit logging, and PII handling
  • Own observability:
    Monte Carlo, lineage, alerting and the SLAs we publish — and drive incidents to root cause and to a durable fix
  • Champion infrastructure as code and automation (Terraform, Git Lab CI, Git Ops) across everything the team runs
What you own vs. our Analytics Engineers

You own the platform: ingestion, storage, orchestration, compute, access control, observability and the frameworks on top of them. Our Analytics Engineers own the business‑facing layer — dbt models, golden datasets, metric definitions and the semantic layer — and consume your platform as a service. You’re energized by multiplying other people’s speed, and…

Position Requirements
10+ Years work experience
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