The ASICS Apps provide digital services and goods focused on helping runners and running events every step of the way. To strengthen our commitment to runners, we are expanding our investment in endurance-related digital services, such as endurance event technology (Race Roster), leading mobile running app (the ASICS Runkeeper app), and other exciting platforms that will help us better serve the endurance industry. Combined, these projects and products makeup ASICS Apps. Movement is an important element in living longer healthy lives, in feeling more fulfilled, and in crossing national and cultural boundaries to bring the world together. If you are looking to join a fun and innovative company focused on the booming digital health and fitness industry, this is the place for you We are building our enterprise data platform from the ground up, and we are looking for a Senior Data Platform Engineer to partner directly with our Data Architect to turn a greenfield vision into an enterprise-grade reality. In this foundational role, you won't be maintaining legacy technical debt, you will be laying down the very first lines of code and infrastructure for our data ecosystem. Crucially, you recognize that data engineering is not just about building pipelines; You will bridge the gap between technical ingestion and business value
- ensuring we collect, structure, and model the right data to power insights for Race Roster and our customers, while keeping our cloud platform cost-efficient and lean. The successful candidate for this role can be either a remote employee (working 100% remotely from a designated location within Canada), a hybrid employee (flexibility to work in the office or from home at a location within 75 km from the London, ON office), or an in-office employee at our London, ON office.



Partner with the Data Architect and help build our greenfield medallion data architecture and data models that will empower internal users and customers with actionable insights around participant growth, revenue over time, registration dynamics, pricing tiers, and event performance. Design compute and storage architectures in Snowflake with financial discipline from Day 1
- optimizing query performance, warehouse utilization, and storage patterns to maximize platform ROI and prevent runaway costs. Build our first generation of ELT ingestion pipelines using Python frameworks like dlt (data load tool) to extract raw data from AWS RDS, third-party APIs, and webhooks into Snowflake, preserving raw data states to guarantee clean data lineage. Layered transformation pipelines: Build our bronze → silver → gold transformation flow as small, focused, easy-to-understand Snowflake Dynamic Tables
- exposing only the curated gold layer to our BI tool (Metabase) and downstream consumers. Snowflake foundation & observability: Bake quality into the platform using Snowflake Data Metric Functions (DMFs), native data lineage tracking, and Dynamic Data Masking. AI/ML integration infrastructure: Build the foundational pipelines required to feed Race Roster’s AI initiatives
- supporting custom model training workflows, feature stores, and cloud AI service integrations (e.g., Fast local analysis & data apps:



Leverage Python notebooks (Jupyter, marimo), DuckDB, and Parquet/Arrow for rapid local prototyping, paired with Streamlit or Gradio to build lightweight prototype data apps and dashboards that turn complex analysis into clear stories for stakeholders. AI-accelerated engineering: Actively integrate AI coding assistants and LLM-powered SQL/Python generation into your daily workflow to accelerate platform buildout, write tests, and document systems as we build them. 5+ years of data engineering experience with a demonstrated focus on business outcomes over raw plumbing . Proven ability to ask "Why are we building this dataset and what actionable story does it tell?" before writing code. ~ Architectural cost discipline: Hands-on experience managing and optimizing cloud infrastructure costs (FinOps), particularly around Snowflake warehouse sizing, query profiling, and auto-suspend configuration. ~ Establish clean engineering standards around FinOps, data lineage, and data quality as foundational practices. ~ Modern ELT & data modeling: Proven ability to translate complex source systems into explicit architecture and data flow diagrams, then build clean dimensional or domain-driven data models ready for storytelling. ~ Expert SQL: Advanced SQL fluency
- window functions, CTEs, semi-structured data (JSON/VARIANT), and reading query profiles to diagnose and optimize slow or expensive queries. ~ Strong hands-on experience with Snowflake core concepts, streaming ingestion patterns, performance tuning, and native governance features (DMFs, lineage, dynamic masking). ~ Experience orchestrating and scheduling data pipelines
- with Snowflake Tasks and Energetic Tables refresh, or external tools like Airflow, Dagster

📌 Data Platform Engineer, Full Stack (London)
🏢 Race Roster
📍 London