Data Platform Engineer

Optable is a Canadian SaaS identity management and data collaboration platform designed for the advertising ecosystem in the age of privacy. Inspired by the radical transformation in how data is governed, connected, and used, Optable was built by veterans of the ad tech industry to address the need for a new generation of privacy-safe advertising products. We are a rapidly growing, venture-backed startup that values execution, innovation, and a "no jerks" policy. Our team embraces a culture of ownership, humility, and initiative to solve tough technical and business challenges.

We're looking for a passionate and experienced technical minds to join our close-knit team. You'll collaborate with colleagues who are dedicated to teaching and learning about software development.

‍

Design, build, and operate reliable and scalable data pipelines and infrastructure that power internal analytics and business intelligence at Optable. This includes developing Spark-based ETLs and maintaining a high-quality data warehouse used by Engineering, Product, Sales, and Customer Success teams. Maybe others as well.

• Build and maintain batch Spark jobs on k8s to ingest and transform data from internal services and external integrations.
• Implement resilient, testable, and performant Spark code (Scala).
• Write high-quality data contracts and schemas with clear ownership and versioning.
• Help design and evolve the core data warehouse schema optimized for BI and analytics.
• Collect feedback from the clients of this product (Solutions, Sales, Product, etc) to understand reporting needs and help prioritize a backlog.
• Use DAG orchestration (with Astro, a Managed Airflow service) for productizing pipelines.

• Set up robust monitoring and alerting for data freshness, pipeline health, and SLA adherence (Prometheus metrics, Grafana Cloud for vizualisations, Grafana IRM for incidents).
• Debug and resolve data quality issues proactively.
• Be ready to participate actively in incident response related to data infrastructure.
• Document pipelines and datasets to support self-serve access and discovery.
• Contribute to internal tooling and CI/CD workflows to improve developer velocity and platform stability.

• 3+ years of experience in data engineering or related fields.
• Strong software engineering fundamentals (version control, CI, testing, modularity).
• SQL fluency and experience with data modeling for BI, reporting, and analytics.
• Familiarity with cloud-native infrastructure on GCP (like GKE) and distributed query engines (BigQuery, Snowflake, SparkSQL, etc.)

• Experience with Golang.
• Prior experience in customer-facing or solution architecture roles (understanding real-world data needs).
• Experience with analytics engineering tools (like Looker)
• Interest in CI/CD for data (e.g., automated testing, data diffs, schema validation).

Downtown Montreal, QC (close to Place des Arts metro station). This role offers a hybrid remote work model; an ideal candidate is expected to be in the office a few days a week. The candidate must be located in the Greater Montreal Area.

• Competitive compensation package, including potential participation in the option pool.
• Extensive healthcare and dental coverage.
• Lots of office perks
• Powerful MacBook Pro provided for local development.
• Opportunity to work on a cutting-edge platform with a talented team.
• Collaborative and supportive work environment within a rapidly growing, venture-backed startup.

If you are a passionate data engineer looking for a challenging and rewarding opportunity in the ad tech space, and you embrace a "no jerks" policy, we encourage you to apply Let's see if we can work together.

‍