Job Description
What is the chance?
RBC is building modern analytics capabilities centered on cloud data platforms, semantic layers, and self-service analytics. Our goal: create data products that serve distinct business domains across the organization.

You'll work across data engineering, analytics, data science, product teams and internal business users, translating requirements into robust analytics solutions. You're the technical problem-solver who turns product direction into working data products that drive decisions. You are an individual contributor working as part of a small team of business insight professionals in a matrixed agile framework.

The upside: Ship solutions that matter. Collaborate with sharp people. Solve complex technical and analytical problems. If you're passionate about building things that work and create real impact, this is the role for you.

What will you do?
Design and build analytics solutions : Uncover product requirements and translate them into end-to-end analytics solutions, data models, transformations, semantic layers, and consumption patterns. Drive quality and maintainability.

Solve technical and analytical problems : Navigate complex data scenarios. Find elegant solutions to tricky modeling challenges. Make trade-offs and move forward.

Enable self-service analytics : Support semantic model delivery and data contracts that let analysts independently use trusted data. Reduce friction and eliminate bottlenecks.

Collaborate effectively : Work with data engineers, governance experts, analysts, data scientists,



product teams and internal business users. Understand their needs. Communicate constraints and possibilities clearly. Establish ownership and accountability of data to reduce ambiguity and clarify decision making.

Support technical standards : Support semantic model building, documentation and consumption. Lead best practices for dimensional design, metric governance, and data quality. Your work drives how the organization thinks about metrics and analytics. Mentor on best practices, advocate for consistency and quality.

What do you need to succeed?
Must-Have:
Semantic layer expertise is non-negotiable : 2+ years with analytics platforms and hands-on experience in semantic layers (dbt, Cube.js, Looker Semantic Layer, or similar). You have proven experience in building solutionsthat drive decisions. You understand dimensional data modeling, data contracts and how to make metrics consistent and discoverable. You know what works at scale, what creates debt

Hands-on modern data stack experience : You've worked with dbt (or another transformation tool), cloud data warehouses (Snowflake, Databricks, BigQuery), and semantic layer concepts (dbt, Cube.js, Looker, etc.). You understand how these pieces fit together.

Outcome-focused problem solver : You think about impact, not output. You're comfortable with ambiguity and make sound decisions with incomplete information. You iterate and move forward. You care about code quality, maintainability, and how others will use what you build.

Clear communicator : You

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📌 Manager, Analytics Engineer (Ontario)
🏢 Socket.dev
📍 Ontario