Analytics Platform & Reliability Engineer

Rumble - Career Page•Toronto, ON

17h•CA$100,000 - CA$120,000

About The Position

Rumble is building the analytics and data platform that powers executive decision-making, operational intelligence, and product insights across the company. As we scale our data infrastructure and expand self-service analytics, we need a platform engineer to own the reliability, performance, and operational excellence of the systems that make it all work. As Analytics Platform & Reliability Engineer, you will own the uptime, performance, and evolution of Rumble's analytics stack—including Apache Superset, Apache Doris, Trino, DuckDB, OpenMetadata, and n8n automation workflows. This is a high-impact infrastructure role: you will maintain production systems, establish SLOs, optimize query performance, and build the operational foundation that enables analysts, engineers, and executives to move fast with confidence. You'll partner across teams—working with data engineering on warehouse architecture, Rumble Ad Center (RAC) on ad-ops integrations, and Rumble engineering on system interoperability. This isn't just operational work: you'll lead tool evaluations, manage production rollouts, and shape the platform's long-term direction under the mentorship of Rumble's technical leadership.

Requirements

3–5 years of experience in analytics, platform, or data engineering roles, including at least 1–2 years managing production-grade BI platforms.
Direct experience administering Apache Superset (or similar tools like Tableau or Looker) in production, with a focus on RBAC, governance, and semantic layers.
Proven track record of defining and maintaining SLOs using observability tools such as Prometheus, Grafana, or Datadog.
Expertise in MPP/OLAP engines, specifically Apache Doris or alternatives like ClickHouse, alongside mandatory Trino or Presto experience.
Advanced SQL skills and query optimization capabilities, including the ability to interpret query plans for performance improvements.
Working knowledge of embedded engines like DuckDB and operational databases such as Postgres or MySQL for metadata storage.
Familiarity with automation and orchestration tools such as n8n, Airflow, or Dagster, as well as REST API integration.
Strong fundamentals in Python, Git, Docker, Kubernetes, and CI/CD pipelines.
Demonstrated ability to work cross-functionally with various lines of business, using strong analytical and collaborative skills to resolve complex technical challenges.

Nice To Haves

Experience with OpenMetadata or a comparable data catalog (DataHub, Amundsen, Atlan).
Familiarity with dbt and modern data-modeling practices.
Exposure to streaming systems (Kafka, Pub/Sub) for near-real-time analytics.
Background in ad-tech, brand safety, or content moderation domains.
Experience with FinOps practices and cloud cost optimization for analytics workloads.

Responsibilities

Own the stability, performance, and operational health of the analytics platform ecosystem—Superset, Doris, Trino, DuckDB, OpenMetadata, n8n, and their metadata backends.
Define, track, and publish SLOs for dashboard P95 latency, Superset uptime, and n8n workflow execution success; lead incident response and root-cause analysis.
Optimize Doris and Trino performance through query tuning, workload management, and resource planning to reduce cost and improve speed.
Build and maintain the Superset semantic layer, including RBAC, certified datasets, connection governance, and metric definitions.
Manage infrastructure-as-code, containerized deployments, version upgrades, and disaster recovery for analytics tooling.
Design and deploy n8n automation workflows for cross-functional business units; maintain CI/CD pipelines for workflow code and infrastructure.
Collaborate with data engineering on warehouse modeling, RAC on ad-tech integrations, and Rumble engineering on cross-system APIs and data contracts.
Enforce security, compliance, and governance standards—audit logging, access control, PII protection, and data quality monitoring.
Empower the analyst and engineering communities through self-service tooling, onboarding documentation, performance audits, and office hours.