Senior Data Platform Developer in Montréal

About Dialogue

Dialogue is the #1 virtual care provider in Canada.

By developingour Integrated Health Platform, we provide exceptional online health and wellness programs (primary care, mental health, i CBT, 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
• Excellence

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.

AI Disclosure Statement

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.

Your role as Senior 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 Saa S 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 Circle CI 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 independently build, deploy, and maintain data products.

• Own the full lifecycle.

Operate in a full Dev Ops model — development, testing, operations, observability and support for the systems you build.

Participate in code reviews and technical design discussions to ensure high-quality of team output.

• We’d love to hear from you if you have
• 3+ years of experience in building production data systems, with deep expertise in large-volume data pipelines, databases and real-time events.
• Strong experience with data warehouse modelling, performance optimization and semantic layer development.

Ability to design, optimize and provide guidance on building scalable data products.

• Strong background with Snowflake and dbt.
• Proficiency with Apache Airflow for workflow management and building resilient pipelines.
• Experience synchronizing data from multiple data sources such as Saa S, Cloud DB’s, APIs and event streams.
• Advanced SQL skills and strong software engineering skills in Python.
• Experience embedding data validation, data observability and idempotent design into deployment pipelines. Familiarity with tools like Datadog or Elementary or Soda.
• Hands‑on experience using AI tools to automate repetitive data workflows such as model and semantic layer development, versioning and deprecation.
• Hands‑on experience setting up continuous integration and deployment workflows using Circle CI or Git Hub Actions for data repositories.
• Proven track record managing cloud resources and environments using Terraform.
• You take pride in what your team accomplishes, not just your individual output, and communicate with clarity and openness.
• The ability to clearly articulate technical designs, project status, and risk to both technical peers and non-technical stakeholders.
• Nice To Have
• Experience with stateful, distributed workflow orchestration engines like Temporal.
• Experience in guiding event emission teams on best practices to support building data products.
• Experience designing AI workflows to simplify data product development lifecycle.
• Experience with data governance frameworks and data catalogs that keep large-scale data assets discoverable.
• Experience with code‑first BI platforms (e. g., Evidence, Looker/Look ML).
• At Dialogue, your well-being is our priority

Benefits

• Access to the Dialogue app and virtual mental health support for you and your family
• Fully funded insurance, a health spending account, dental coverage, and fitness reimbursement
• 4 weeks vacation, 9 wellness days, and 1 volunteer day
• Hybrid work: 3 days/week in our Montreal or Toronto offices, excluding remote roles
• Work abroad up to 4 weeks/year
• Incentive plans, referral bonuses & RRSP matching
• Learning via Coursera, external training budget & mentorship
• Optional parental leave top‑up

The posted salary range represents the expected hiring range for this role.

At Dialogue, where a candidate's offer lands within the range is determined by relevant experience, demonstrated skills, and qualifications.

• The Pay Range For This Role Is
• 105,400 - 125,115 CAD per year (Montreal Office (HQ))
• #J-18808-Ljbffr