Senior Platform Data Engineer — Lakehouse & Automation

Engg; San Francisco (CA); On-site; USD 150,000 - 200,000; Full time

Job summary

Aircall is seeking a Senior Data Engineer to lead platform-driven data infrastructure, enabling analytics teams to build faster on scalable lakehouse technologies. You will own ingestion, storage, and governance, collaborating with data scientists and engineers to ensure reliability and performance.

You will drive end-to-end data pipelines, implement IaC and CI/CD practices, and partner with AI workflows to support real-time analytics and decision making.

Qualifications

• 4+ years in data engineering, data platform or infra engineering.
• Strong Python and SQL, with experience building reusable frameworks.
• Production experience with an orchestration framework at scale (Airflow, Dagster, Prefect).
• Hands-on Apache Spark and distributed systems fundamentals.
• Deep AWS experience (S3, EKS/ECS, IAM, Glue/Athena).
• Familiar with Kubernetes, Docker, and CI/CD, IaC (Terraform).
• Track record owning reliability: SLAs, monitoring, on-call.
• Daily use of AI coding tools as part of infrastructure work.
• Excellent cross-functional communication.

Responsibilities

• Build and operate the lakehouse with Apache Iceberg on S3.
• Own ingestion end to end: Flink CDC → Kafka → Iceberg; ensure freshness.
• Manage compute/orchestration: Kyuubi on EKS, Airflow migration, autoscaling.
• Create self-service tooling so analytics engineers own pipelines.
• Close environment gaps with staging, CI, schema changes, gating.
• Own governance: Lake Formation RBAC, SSO, audit logging, PII handling.
• Own observability: Monte Carlo, lineage, alerting, SLAs.
• Champion infrastructure as code (Terraform) and GitOps.

Skills

Python

SQL

Distributed systems

AWS

Kubernetes

CI/CD

AI coding tools

Cross‑functional communication

Tools

Airflow

Dagster

Prefect

Spark

Kubernetes

Docker

Terraform

Git

Job description

Aircall is seeking a Senior Data Engineer to lead platform-driven data infrastructure, enabling analytics teams to build faster on scalable lakehouse technologies. You will own ingestion, storage, and governance, collaborating with data scientists and engineers to ensure reliability and performance.

You will drive end-to-end data pipelines, implement IaC and CI/CD practices, and partner with AI workflows to support real-time analytics and decision making.