Data Platform Engineer

About the role

The Data Platform Engineer will own the reliability and operational performance of large‑scale distributed systems and data infrastructure at Chainlink, strengthening production streaming and Kubernetes workloads while ensuring repeatable, version‑controlled operations.

Key responsibilities

• Enable critical product initiatives by delivering streaming and data infrastructure for CRE, CCIP, Data Feeds and Data Streams, translating product requirements into reliable Redpanda/Kafka and Flink capabilities.
• Maintain 99.9% availability of critical data infrastructure, scaling streaming and Kubernetes workloads, resolving throughput and recovery bottlenecks, and defining SLIs.
• Reduce operational maintenance to below 20% of team capacity through automation, actionable alerts, tested recovery procedures and repeatable vulnerability remediation.
• Connect Redpanda topic traffic, Flink processing and BigQuery usage to consuming teams, making consumption accountable and cost‑effective.
• Build reusable Terraform modules, deployment workflows and documentation to enable self‑service provisioning, testing, scaling and retiring of AWS and Kubernetes resources.

Required profile

• Proven experience operating large‑scale distributed systems, streaming platforms and data processing infrastructure with deep understanding of availability, consistency, failure modes and performance trade‑offs.
• Experience deploying, operating and troubleshooting production Kubernetes workloads, including resource management, scaling and safe rollouts.
• Experience building reusable infrastructure modules, self‑service capabilities and CI/CD workflows that enable engineering teams to deploy and operate services independently.

Required skills

• Apache Flink, Redpanda/Kafka, Iceberg, PostgreSQL, Airflow, Trino.
• Kubernetes, Terraform, AWS (Aurora/RDS, BigQuery), Java, Go.