Senior Data Platform Developer

Dialogue is the #1 virtual care provider in Canada. By developing our Integrated Health Platform, we provide exceptional online health and wellness programs (primary care, mental health, iCBT, EAP, and wellness) to organizations that want to improve the wellness of their employees and families.

When it comes to our work, we set the bar high. Together, we’re transforming health and helping millions improve their well‑being. We’re firm believers that great people don’t settle on:

• Impact
• Community
• Growth

Feel like you can make a difference? Good news, we saved you a seat

Come as you are. As a proud equal‑opportunity employer, Dialogue is dedicated to creating a diverse and inclusive workplace for everyone. Qualified applicants will be considered regardless of citizenship, ethnicity, race, colour, religion, gender, gender identity or expression, sexual orientation, disability, age, or veteran status. Applicants who require specialized accommodation are encouraged to contact accessibility@dialogue.co .

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To ensure an efficient and fair review process, we utilize artificial intelligence tools to assist in the initial screening and assessment of applicants for this role.

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Your role asSenior Data Platform Developer

We are looking for a Senior Data Platform Developer that is excited to design, build, and maintain our modern data platform. In this role, you will define and implement engineering best practices across the full data lifecycle, from ingestion and transformation to consumption. The goal of the team is to build a stable and scalable platform that empowers power users across the organization to build data products and accelerate time from data to insights.

Additionally, this role would partner with data and analytics related functions across Product, Sales, Ops, Finance and other teams to onboard power users into a self serve model. The team also owns relationship with relevant technology vendors and identifies opportunities to improve vendor product.

What you’ll be doing

• Data Ingestion & Orchestration: Design scalable ingestion frameworks for batch and streaming data. This can be standard SaaS sources, API end points, internal DB’s or our own event system. Orchestrate robust and resilient data pipelines utilizing Airflow (with opportunity to evaluate/implement workflows with Temporal).
• Data Modelling & Semantic Layer Development: Define and enforce data modelling standards — including dimensional modelling, semantic layer development and streaming analytics. Enable software and analytics engineers to author their own transformations to production‑grade standards.
• Data Quality & Observability: Embed data validation, testing, and observability into every stage of the pipeline — from ingestion through transformation to consumption. Define testing standards for dbt models, set up monitoring and alerting to ensure data products fail loudly and actionably rather than silently.
• AI‑Assisted Engineering Workflows: Design and implement AI‑assisted workflows to accelerate repetitive data product development lifecycle and ensure AI agents have accurate context and sufficient guardrails for analytics.
• CI/CD & Infrastructure as Code: Provision, manage, and scale infrastructure using Terraform . Build and maintain robust CI/CD pipelines using CircleCI for automated testing, PR checks, validation, and deployment.
• Data Storage & Access Control: Optimize our Snowflake warehouse for performance and cost efficiency. Implement granular Access Management, column‑level masking, and strict data governance policies.
• BI Tool Ownership: Own Evidence as a deployed tool — infrastructure, hosting, Snowflake connectivity, upgrades, and CI/CD. Enable teams to build and deploy their own data products on it.
• Shared Technical Leadership : Partner with our developers sharing context, translating ambiguous requirements into clear architecture, aligning on technical decisions collaboratively, and building on each other’s work.
• Non‑Technical User Enablement: Guide software and analytics developers on adopting production‑grade standards; create documentation and tooling that makes adherence the path of least resistance. Train and up skill data power users so they can inde