高级数据平台工程师
Senior Data Platform Engineer
Mirantis,IREN公司旗下,是一家基于Kubernetes的AI基础设施公司,帮助组织构建和运营可扩展、安全且自主的基础设施,用于现代AI、机器学习和数据密集型应用。通过结合开源创新与对Kubernetes编排的深入专业知识,Mirantis使平台工程团队能够在任何环境中——本地、云上、边缘或自主数据中心——交付可组合、生产就绪的开发者平台。随着企业应对日益复杂的AI驱动工作负载,Mirantis提供所需的自动化、GPU编排和策略驱动的控制,以自信和敏捷的方式管理基础设施。致力于开放标准并避免供应商锁定,Mirantis确保客户对其基础设施战略拥有完全控制权。
https://www.mirantis.com/
我们正在寻找一位经验丰富的数据平台工程师,负责k0rdent-ai平台背后事件流的核心架构——企业GPU基础设施的多租户控制平面。每个集群的创建、每个小时GPU的使用以及每个租户的操作都会产生事件,这些事件必须可靠地从我们的服务传输到分析、计费、可观测性和下游系统。你将从端到端设计和运营该数据管道:流媒体平台本身、为其提供数据的连接器和变更数据捕获流程、保持生产者和消费者兼容性的模式,以及让产品团队能够自助接入而无需等待你的自动化工具。在敏捷框架下,与分布在北美、欧洲和印度的工程团队协作,你将使事件数据成为一种可靠的产品表面,而非一种尽力而为的辅助通道。
主要职责:
· 在Kubernetes上设计、部署和运营生产级流媒体平台——集群生命周期、主题、分区和保留策略、容量规划和升级。
- 构建和维护在操作数据库、流媒体层和分析存储之间移动数据的变更数据捕获和连接器管道。
- 负责模式治理——模式注册表、兼容性规则和版本控制规范,确保生产者更改不会静默破坏消费者。
- 在现成组件不足时,用Java或Go开发自定义连接器、转换逻辑和流处理代码。
- 构建自助接入功能,使产品团队可以通过信息文档自行配置主题、模式和访问权限。
查看英文原文
Mirantis, an IREN company, is the Kubernetes-native AI infrastructure company, enabling organizations to build and operate scalable, secure, and sovereign infrastructure for modern AI, machine learning, and data-intensive applications. By combining open source innovation with deep expertise in Kubernetes orchestration, Mirantis empowers platform engineering teams to deliver composable, production-ready developer platforms across any environment—on-premises, in the cloud, at the edge, or in sovereign data centers. As enterprises navigate the growing complexity of AI-driven workloads, Mirantis delivers the automation, GPU orchestration, and policy-driven control needed to manage infrastructure with confidence and agility. Committed to open standards and freedom from lock-in, Mirantis ensures that customers retain full control of their infrastructure strategy. https://www.mirantis.com/
We are looking for an experienced data platform engineer to own the event-streaming backbone behind the k0rdent-ai platform — the multi-tenant control plane for enterprise GPU infrastructure. Every cluster provisioned, every GPU-hour consumed, and every tenant action produces events that must move reliably from our services into analytics, billing, observability, and downstream systems. You will design and operate that pipeline end to end: the streaming platform itself, the connectors and change-data-capture flows that feed it, the schemas that keep producers and consumers compatible, and the automation that lets product teams onboard themselves without waiting on you. Working within an agile framework alongside engineering teams across the US, Europe, and India, you will make event data a dependable product surface rather than a best-effort side channel.
Main Responsibilities:
· Design, deploy, and operate the production streaming platform on Kubernetes — cluster lifecycle, topics, partitioning and retention strategy, capacity planning, and upgrades.
- Build and maintain change-data-capture and connector pipelines moving data between operational databases, the streaming layer, and analytical stores.
- Own schema governance — a schema registry, compatibility rules, and versioning discipline so producer changes never silently break consumers.
- Develop custom connectors, transformations, and stream-processing logic in Java or Go where off-the-shelf components fall short.
- Build self-service onboarding so product teams can provision topics, schemas, and access through infrastructure as code rather than tickets.
- Automate the platform with Terraform and GitOps — no manually configured clusters, no undocumented topic definitions.
- Instrument the pipeline for production: metrics, lag and throughput monitoring, alerting, and dashboards that both the platform team and application owners can act on.
- Enforce security and multi-tenant isolation across the streaming layer — mTLS, authentication, topic-level RBAC, encryption, and audit trails.
- Guarantee delivery semantics that the business can rely on — ordering, idempotency, exactly-once where required, replay, and disaster recovery.
- Partner with backend and SRE teams on event schema design, producer patterns, and failure modes; participate in on-call for the platform you own.
- Mentor engineers on streaming architecture and raise the team's bar through design review and documentation.
Required Skills/Abilities:
· 10+ years in software, data, or platform engineering, including deep hands-on ownership of a production event-streaming platform.
- Expert-level Apache Kafka (or Confluent Platform/Cloud) — administration, tuning, troubleshooting, and capacity management at production scale.
- Strong Kafka Connect and CDC experience — Debezium, JDBC, and custom connector or transformation development.
- Proven schema-registry practice and compatibility management across many independent producers and consumers.
- Solid programming ability in Java, Python, or Go — enough to build connectors, transformations, and platform tooling, not only configure them.
- Strong SQL and relational database knowledge (PostgreSQL, MySQL, or equivalent), including replication and CDC mechanics.
- Kubernetes fluency — deploying, operating, and debugging stateful workloads.
- Infrastructure as code discipline (Terraform or equivalent) and CI/CD pipeline ownership.
- Clear written English for design docs, runbooks, and asynchronous review across global time zones.
Must Have
· Streaming: Apache Kafka or Confluent, Kafka Connect, Schema Registry, and stream processing.
- Data Movement: CDC tooling (Debezium or equivalent), connector development, and pipelines into analytical stores.
- Kubernetes Native: Kubernetes, Docker, and Helm-packaged workloads in production.
- Automation: Terraform, CI/CD (Jenkins, GitHub Actions, or equivalent), and GitOps practice.
- Data Stores: PostgreSQL at scale, plus at least one cloud data warehouse or search store (Snowflake, BigQuery, Elasticsearch, or equivalent).
- Cloud: AWS or GCP — networking, IAM, managed Kubernetes.
- Security & Observability: mTLS, OIDC/SSO, RBAC, and Prometheus/Grafana monitoring.
Nice to Have
· Confluent certification, or contributions to Kafka-ecosystem open source.
- Stream processing with Flink, Kafka Streams, or ksqlDB.
- Event-driven architecture patterns — outbox, saga, event sourcing, CloudEvents.
- Exposure to GPU infrastructure, AI/ML data pipelines, or telemetry at high cardinality.
- Usage metering, billing, or chargeback pipelines built on event data.
- Alternative brokers (NATS JetStream, Pulsar) and a view on the tradeoffs.
- Go, for working directly in our backend services' producer code.
- Data quality, lineage, or catalog tooling.
- Compliance exposure — SOC 2, ISO 27001, or similar audit support.
Education and Experience:
· Bachelor’s degree in Computer Science & Engineering or related field or 10 years related experience.
What does Mirantis offer you?
· Work with an established Silicon Valley leader in the cloud infrastructure industry;
· Work with exceptionally passionate, talented and engaging colleagues, helping Fortune 500 and Global 2000 customers implement next-generation cloud technologies;
· Be a part of cutting-edge, open-source innovation;
· Thrive in the high-energy environment of a young company where openness, collaboration, risk-taking, and continuous growth are valued;
· Professional development and training;
· Attend conferences and working groups;
· Company outings, happy hours, hackathons, and tech talks;
· Receive a competitive compensation package with a strong benefits plan.
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