Data & ML Platform Engineer (Hybrid)

Homebase, Inc.; Toronto; On-site; CAD 110,000 - 160,000; Full time

Benefits offered by this job

Stock options

TFSA/RRSP with 4% company match

Comprehensive health insurance

Job summary

Homebase, Inc. in Toronto is seeking an experienced data engineering / ML platform engineer to own data-in, the data platform, and the model-serving layer. You will drive real-time and batch data workflows and help scale AI-driven features for the Homebase platform.

You will collaborate with data engineering, data science, and product engineering teams, contribute to the feature store and MLflow practices, and participate in Toronto-based in-office days on Tuesdays and Wednesdays.

Qualifications

• Production experience with distributed streaming systems (Kafka and CDC).
• Hands-on Spark and Delta experience.
• Strong Python and SQL.
• Experience with container infrastructure (Docker, ECS, or Kubernetes).
• Infrastructure-as-code experience, ideally Terraform.
• Comfort being part of an on-call schedule.
• AI fluency: you already experiment with AI tools in your engineering workflow and can share what you learned.
• Comfort moving quickly through ambiguity, with clear communication across technical and non-technical teams.
• An ownership mindset: you stay close to the details and stand behind the systems you build.
• The ability to collaborate in person at our Toronto hub every Tuesday and Wednesday, and to use that time for fast decisions and shared context.
• Unity Catalog governance.
• MLflow and feature stores.
• LLM-serving experience.

Responsibilities

• Own data-in: build CDC and streaming pipelines and SLAs.
• Own the data platform: Databricks, Unity Catalog, warehouses, Terraform.
• Build the serving layer: ship gRPC services and real-time inference.
• Grow ML foundations: evolve feature store and MLflow with data science.
• Be AI-first: use AI tools to accelerate development and ops.
• Partner across teams: collaborate with data eng/DS/pc engineering.
• Share the on-call: participate in rotation and improve reliability.

Skills

Data engineering

Python

SQL

Spark

Kafka

Delta Lake

LLM serving

ML concepts

Tools

Databricks

Unity Catalog

Terraform

Docker

Kubernetes

ECS

Job description

• Toronto - P2 Toronto - P2 CA$110K – CA$130K Offers Equity
• Toronto - P3 Toronto - P2 CA$130K – CA$160K Offers Equity

We believe compensation should be fair, transparent, and reflective of impact. At Homebase, compensation is based on role level, skills, and performance. During the interview process, we evaluate experience, scope, and impact to determine the appropriate level for the role, which maps to a defined salary range. Posted ranges reflect the expected starting range for the role, and offers are made within that range, with flexibility based on experience, market context, and leveling. As impact grows, so does compensation over time.

At Homebase, you’ll join a team that’s bold, fast-moving, and obsessed with helping small businesses thrive. We build with empathy, act with urgency, and take big swings that drive real-world impact. Here, every Homie shows up to raise the bar, support one another, and celebrate wins as a team.

We’re not just building an app—we’re building unstoppable teams. So what do you say, are you in?

Your Impact Starts Here

Every data and AI feature at Homebase runs on the platform you’ll help build. Our AI-powered product work is moving fast, and the platform underneath it has to move faster. You’ll be one of two engineers who carry that build.

You’ll own how data gets in, how the platform runs, and how models and data get served back to the product, with real ownership from day one.

These are the key ways you’ll contribute and create impact in this role:

• Own data-in. Build and run CDC and streaming pipelines (Kafka, Debezium, Spark streaming into Delta), including replay, restream, and ingestion SLAs.
• Own the data platform. Manage Databricks, Unity Catalog, warehouses, and Terraform, with CI/CD and DAB deploys for data infrastructure.
• Build the serving layer. Ship gRPC services, move batch workloads to real-time inference, and make LLM latency and cost visible.
• Grow the ML foundations. Evolve our feature store and MLflow practice, and work with data science to take proofs of concept to production.
• Be AI-first in how you build. Use AI-assisted tools to build, test, and operate faster, experiment with new capabilities, and share what works with the team.
• Partner across teams. Work with data engineering, data science, and product engineering to turn customer needs into reliable systems.
• Share the on-call. Join the team’s on-call rotation, which has its own escalation path, and help make it quieter over time.

The Foundation for Success -

These are the experiences and strengths that will set you up for success in this role:

• Production experience with distributed streaming systems (Kafka and CDC).
• Hands-on Spark and Delta experience.
• Strong Python and SQL.
• Experience with container infrastructure (Docker, ECS, or Kubernetes).
• Infrastructure-as-code experience, ideally Terraform.
• Comfort being part of an on-call schedule.
• AI fluency: you already experiment with AI tools in your engineering workflow and can share what you learned.
• Comfort moving quickly through ambiguity, with clear communication across technical and non-technical teams.
• An ownership mindset: you stay close to the details and stand behind the systems you build.
• The ability to collaborate in person at our Toronto hub every Tuesday and Wednesday, and to use that time for fast decisions and shared context.
• Unity Catalog governance.
• MLflow and feature stores.
• LLM-serving experience.

The Homie Way -

• Be Customer Obsessed – Solve problems with empathy and creativity.
• Move Fast, Learn Fast – Experiment, take action, and grow every day.
• Own Your Impact – Think big, focus on what matters, and make decisions you stand behind.
• Master Your Craft – Excellence fuels impact—show up, step up, and make your mark.
• Win Together – Put goals over roles, lead with trust, and connect to our mission and each other.

What We Offer

• Ownership & Savings: Stock options + TFSA/RRSP with 4% company match
• Health & Wellness: Comprehensive medical, dental, and vision for you and your dependents
• Paid Time Off: Flexible PTO + company holidays + designated focus periods
• AI access, for real: We invest in builders and believe that curiosity shouldn't have a paywall. That means you'll have access to paid AI tools with minimal restrictions, so you can build, experiment, and level up your craft.
• Family Support: Maternity/Parental Leave EI top-up support offered (after 6 months of service)
• Work Your Way: Work From Anywhere Month + meeting-free weeks yearly
• Workspace Perks: Meals provided, team offsites, and Customer Days
• Our Hybrid Rhythm: We believe collaboration drives impact. That’s why Tuesdays and Wednesdays are our required in-office days—a time to move faster as a team, build deeper connections, make better decisions, and build together.

What to Expect During the Interview Process

• Meet the Talent Acquisition team, Mavel W.
• Participate in technical interviews (live coding plus a data and ML platform design conversation)
• Background Check + Offer Stage
• Welcome to the team, Homie

Belonging at Homebase

We're committed to fostering a welcoming space where every Homie can be their full self. Experience comes in many forms—so if you're excited about this role, even if you don’t meet 100% of the qualifications, we encourage you to apply!

Homebase is the everything app for hourly teams—built to simplify the day-to-day and superpower local businesses. With tools for scheduling, time clocks, payroll, communication, HR, and more, we help teams stay connected and in control. Today, over 150,000 small (but mighty) businesses rely on us to make work radically easier. Together, we’ve tracked over a billion hours for 2M+ workers—and we’re just getting started.

At Homebase, we celebrate diversity and are proud to be an equal opportunity employer. We welcome all candidates and do not discriminate based on any legally protected status. If you need accommodations during the hiring process, please let us know—we’re committed to ensuring fair and equitable access for all.