Data Platform Engineer
Senior SRE owning reliability of Chainlink's large-scale data infrastructure: operating Redpanda/Kafka streaming and Flink pipelines, Kubernetes and AWS workloads at 99.9% availability, with Terraform-managed infrastructure, automation, cost accountability and self-service tooling for engineering teams.
- Compensation
- Not disclosed
- Location
- Canada
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Demonstrated experience operating large-scale distributed systems and scalable data processing infrastructure in production
- Operated Kafka or Kafka-compatible streaming platforms such as Redpanda in production, with capacity planning, performance tuning and troubleshooting
- Provisioned and managed production infrastructure using Terraform with version-controlled, reviewed, repeatable changes
- Experience deploying, operating and troubleshooting production Kubernetes workloads, including resource management, scaling and safe rollouts
Nice to have
- Built reusable infrastructure modules, self-service capabilities and CI/CD workflows for engineering teams
- Experience building and operating Apache Flink pipelines in production, including monitoring, diagnosing failures and managing recovery
- Operated AWS Aurora/RDS in production, including provisioning, backup/recovery, failover, rightsizing and cost optimization
- Advanced experience with 1 or more of Apache Flink, Redpanda/Kafka, Iceberg, PostgreSQL, Airflow or Trino
- Experience reading, debugging and writing production-quality code in Java and/or Go
- Contributions to open-source infrastructure or data projects (code, tooling, documentation, bug reports)
Full description
About Chainlink
Chainlink is the industry-standard oracle platform bringing the capital markets onchain and powering the majority of decentralized finance (DeFi). The Chainlink stack provides the essential data, interoperability, compliance, and privacy standards needed to power advanced blockchain use cases for institutional tokenized assets, lending, payments, stablecoins, and more. Since inventing decentralized oracle networks, Chainlink has enabled tens of trillions in transaction value and now secures the vast majority of DeFi.
Many of the world’s largest financial services institutions have also adopted Chainlink’s standards and infrastructure, including Swift, Euroclear, Mastercard, Fidelity International, UBS, S&P Dow Jones Indices, FTSE Russell, WisdomTree, ANZ, and top protocols such as Aave, Lido, GMX and many others. Chainlink leverages a novel fee model where offchain and onchain revenue from enterprise adoption is converted to LINK tokens and stored in a strategic Chainlink Reserve. Learn more at .
About the Role
The Data Platform Engineer will own the reliability and operational performance of large-scale distributed systems and data infrastructure. This role will strengthen the production operation of streaming and Kubernetes workloads while ensuring infrastructure changes are managed through repeatable, version-controlled practices. The role will also improve the scalability and operational efficiency of the infrastructure that engineering teams depend on.
Your Impact
- Enable critical product initiatives to launch on time. Deliver the streaming and data infrastructure required by CRE, CCIP, Data Feeds and Data Streams, translating product requirements into reliable Redpanda/Kafka and Flink capabilities.
- Maintain 99.9% availability for critical data infrastructure as usage grows. Scale streaming and Kubernetes workloads, resolve throughput and recovery bottlenecks, and define SLIs that reflect the experience of consuming services
- Help keep operational maintenance below 20% of team capacity. Reduce recurring incidents, manual interventions and routine maintenance through automation, actionable alerts, tested recovery procedures and repeatable vulnerability remediation.
- Reduce cost to serve and make consumption accountable. Connect Redpanda topic traffic, Flink processing and BigQuery usage to the teams and services consuming them.
- Make infrastructure self-service and safe throughout its lifecycle. Build reusable Terraform modules, deployment workflows and documentation that let teams provision, test, scale and retire AWS and Kubernetes resources independently.
- Use service adoption and consumer needs to guide improvements. Identify who consumes each infrastructure service and which product outcomes depend on it.