Rumble
Data Platform & Analytics Engineer
Toronto
Sponsorship not specified$100k-$120kDetected 50 days ago
Data StructuresSQLPostgreSQLMySQLKubernetesHelmKafkadbtData Engineering
About the role
- Specific vision abilities required by this job include clarity of vision at approximately 20 inches or less (i.e., working with small objects or reading small print), including the use of computers.
Responsibilities
- Design and build derived and "gold" data layers in Doris and Trino that power Superset dashboards and other BI tools, using views, materialized views, and well-structured warehouse schemas.
- Translate high-level, often ambiguous data requests into clear table designs, partitioning strategies, and query patterns that support the analyses teams need to perform.
- Implement and maintain safe data operations: understand how different engines handle DDL/DML operations and table types
- Build and optimize SQL across multiple engines (Doris, Trino/Presto, DuckDB, and others), including performance tuning, explain-plan analysis, and making schema or modeling changes to support efficient querying.
- Collaborate with RAC and search-focused teams on use cases such as identifying searches with no matching content, including solutions that leverage embeddings and vector-based approaches when appropriate.
- Support analysts and product teams by iterating quickly on table structures, metrics, and data contracts, then documenting how to use those assets effectively in Superset and other analytics tools.
- Own a smaller but critical slice of platform administration: install and upgrade Superset, Doris, Trino, DuckDB, OpenMetadata, and n8n on Kubernetes/VMs using Helm, and troubleshoot configuration issues when they arise.
- Implement and maintain safe data operations: understand how different engines handle DDL/DML operations and table types; configure storage, versioning, and cross-region protection so that errors are detectable and recoverable rather than catastrophic.
- you'll design data models, determine how new datasets are brought into Doris and the data lake, build views and materialized views that make BI workflows seamless, and make careful, informed decisions that keep our data accurate, performant, and recoverable as priorities evolve.
Requirements
- 4+ years of experience in data engineering, analytics engineering, or data platform roles, with a strong focus on SQL, data modeling, and database behavior rather than only BI or dashboarding.
- Hands-on experience with data lakes and table formats (Parquet, Hive, Iceberg or similar), and an understanding of how operations such as deletes, compaction, and merges affect underlying files and storage.
- Practical experience with Kubernetes, Helm, and containerized deployments-sufficient to safely install, upgrade, and troubleshoot data tools without compromising data integrity.
- Strong understanding of data durability and safety practices (backups, versioning, replication, restore drills) in cloud storage and database environments.
- While performing the duties of this job, the employee is regularly required to sit for prolonged periods of time while using a computer and/or keyboard.
- The employee is required to communicate verbally and hear.
- The employee may be required to walk, reach with hands and arms, balance, and stoop or kneel.
- The employee may occasionally be required to lift and/or move up to 15 pounds.
- Deep SQL experience across multiple engines (e.g., Trino/Presto, Doris/ClickHouse, Postgres, MySQL), including schema design, complex joins, and performance optimization at scale.
- Proven experience building derived layers (bronze/silver/gold, marts, or similar patterns) for BI and analytics, ideally with dbt or a comparable transformation framework.
- Comfort working with evolving and sometimes loosely defined data requirements, and turning them into stable, well-documented tables and views that are easy to use and maintain.
- Ability to collaborate with analysts and non-technical stakeholders, asking the right questions to design data structures that match how they actually query and use the data.
Nice to have
- 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.
- Why Our Team Loves Working Here:
- we're proud of their success stories
- We enjoy challenging the status quo and going head-to-head against Big Tech
Skills
- Rumble is the Freedom-First technology platform.
- As a Data Platform &
- The salary range listed for this position is a good faith estimate based on experience, qualifications, and internal compensation structure.
- This posting refers to an active vacancy within the organization.
Compensation
- $100,000 - $120,000 CAD base + benefits + equity
- Note: The salary range listed for this position is a good faith estimate based on experience, qualifications, and internal compensation structure.
- The actual salary offered varies depending on the candidate's skill level and experience.
- We pay competitive salaries and provide great benefits
Benefits
- Set up and maintain SLOs and monitoring for query performance, job health, and data quality, and drive or escalate remediation when platform issues impact analytic workflows.
Company info
- We are making a significant financial impact for our video creator community; we're proud of their success stories
- We aren't afraid to try new things; we act fast and want to win
- We pay competitive salaries and provide great benefits
Equal opportunity
- Rumble is an equal opportunity employer.
- We promote an equal playing field where everyone has the same opportunities regardless of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability status, or any other applicable characteristics protected by law.
- Rumble is an active participant in the e-verify program.
- EEO Statement:
This listing is sourced directly from Rumble's careers page and normalized into a canonical job model.