Sr. Data Platform Engineer

Etraveli Group • Toronto, ON

9h • CA$140,000 - CA$170,000 • Hybrid

About The Position

Tripstack is moving its entire data stack from bare-metal VMs to Kubernetes on OpenStack in a new data centre. We are looking for a senior infrastructure engineer who has done stateful migrations before, who can plan, codify, and execute this one safely, and who will own the day-to-day operational health of the data platform once we are there. This is a hands-on platform and SRE role with a clear, time-bounded mission. You will partner closely with our SRE team on networking, hardware, and Kubernetes fundamentals, and own the data applications — Druid, Spark, Redpanda, Airflow, PostgreSQL, Elasticsearch — end-to-end. It is not an ML role. We have a separate plan for evolving our MLFlow platform, and the right hire here may grow into more of that work over time, but day-one impact is the migration and the operational health of the platform.

Requirements

• Strong Kubernetes experience with stateful workloads — StatefulSets, PVCs, pod disruption budgets, and rolling upgrades for data systems. You have done a real stateful migration before and can talk through what went wrong.
• Infrastructure as Code at a senior level — Terraform, Helm or Kustomize, GitOps with ArgoCD or Flux. You have shipped production infrastructure this way, not just experimented with it.
• Observability and RCA discipline — Prometheus, Grafana, distributed tracing, SLOs, error budgets, and the habit of writing the runbook that stops the next incident.
• Production operations experience with at least one of Apache Druid, Apache Kafka or Redpanda, Apache Spark, or Elasticsearch — deep enough to be credible on internals and willing to learn the others.
• 7+ years building and operating production data or platform systems, at least 2 of them on self-hosted or bare-metal infrastructure. You have been on-call for what you built.
• Clear written and verbal English; comfortable working across Kraków, Toronto, Pune, and Stockholm time zones.

Nice To Haves

• Deep Apache Druid production operations — segment lifecycle, JVM tuning, ingestion spec authoring, and RCA on broker/coordinator-class failures.
• Apache Spark at scale — DAG execution, shuffle optimisation, memory tuning, Spark-on-Kubernetes.
• OpenStack familiarity — Neutron networking, Cinder/Ceph storage.
• Fluency with agentic coding tools (Claude Code, Gemini, or equivalent) as a real part of your workflow — including the judgement to know when not to trust an AI-generated config for a production data system.
• Python that is production-grade, plus working knowledge of at least one JVM or Go-family language so you can integrate with our services directly.
• Security and secrets management in Kubernetes — Vault, network policies, encryption at rest.
• Change Data Capture patterns, especially PostgreSQL-to-Druid streaming.
• Delta Lake or Apache Iceberg experience and architectural judgement about when to introduce a table format.
• Exposure to travel, flights, or large-scale search and cache systems.
• Interest in growing into ownership of our MLFlow-based ML platform over time. We have a separate plan for that work, but a curious operator is welcome.

Responsibilities

• Lead the data-stack migration
• Plan and execute the migration of Druid, Spark, Redpanda, and our orchestration layer from bare-metal VMs to Kubernetes on OpenStack, with no downtime on stateful workloads.
• Design StatefulSet, PVC, pod-disruption-budget, and rolling-upgrade patterns that are safe for production data systems.
• Codify the migration with Infrastructure as Code — Terraform for OpenStack, Helm or Kustomize for Kubernetes, GitOps via ArgoCD or Flux — so the result is reproducible and supportable by the whole team.
• Own the operational health of Druid, Spark, Redpanda, Airflow, PostgreSQL, and Elasticsearch as production systems — segment lifecycle, JVM tuning, ingestion specs, broker/coordinator/overlord internals, partition design, consumer lag, replication tuning.
• Build the KPIs, alerting, dashboards, and runbooks that let us see cluster exhaustion before it becomes an incident, and diagnose it quickly when it does.
• Own the query, report, segment, and tiering optimisations that keep our analytics cost-effective and responsive under load.
• Build the Prometheus, Grafana, and distributed-tracing coverage our data systems need. Treat SLOs, error budgets, and post-incident discipline as table stakes.
• Partner with SRE on hardware, networking, and Kubernetes fundamentals — but own the data applications themselves end-to-end.

Benefits

• Opportunity to work with a young, dynamic, and a growing team composed of high-caliber professionals.
• Culture where individuals are encouraged to do more and be more.
• Ambitious mission.
• Embracing diversity.
• Equal opportunity employer.
• Commitment to creating a safe, healthy and accessible environment.
• Accommodations available during the recruitment process.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed