Senior Data Engineer - Machine Learning & Data Platforms - REMOTE
Summary
Senior Data Engineer building scalable Spark/Databricks data pipelines, ETL, and time-series feature engineering for production ML systems at a client turning automotive and industrial data into real-time insights. Full-time remote from Toronto, Ottawa, or Montreal, joining a 13-person engineering team.
Job Description
Job Description
Senior Data Engineer- Machine Learning & Data Platforms | Remote
Our client is building the next generation of industrial intelligence, transforming complex automotive and industrial data into real-time, actionable insights powered by machine learning. This is a FT remote position. You can work from Toronto, Ottawa or Montreal.
We are seeking an experienced Data Engineer who thrives in high-scale, production ML environments and enjoys working with complex, messy datasets to build reliable, scalable data foundations for advanced analytics.
You will join a team of 13 engineers and data professionals, working in a highly collaborative, fast-moving environment. The role is remote-friendly, with strong cross-functional interaction across engineering, data science, and business teams.
What You’ll Do
Design, build, and maintain scalable data pipelines and ETL processes for large structured and unstructured datasets
Develop and optimize Spark-based data workflows supporting production ML systems
Collaborate closely with data scientists, ML engineers, and business stakeholders
Translate complex business needs into scalable, production-grade data solutions
Build feature engineering pipelines for time-series and predictive models
Ensure data quality, governance, security, and reliability across systems
Continuously improve data architecture, performance, and scalability
What You Bring
Min. 6+ years in data engineering or ML data pipeline development
Strong experience with Apache Spark, PySpark, Databricks, Delta Lake
Advanced skills in Python, SQL, and Airflow
Deep understanding of Medallion architecture and ETL design patterns
Experience building time-series features (rolling windows, lags, trend indicators)
Ability to work closely with ML teams and translate data into model-ready structures
Bachelor’s or Master’s in Computer Science, Engineering, or related field
⭐ Preferred Experience - we will highly consider candidates with below skills;
Background in retail, e-commerce, or supply chain environments dealing with large, messy, high-volume datasets
Experience working directly with machine learning teams or supporting ML model development
Hands-on experience in forecasting, demand planning, or similar data-heavy business domains
Experience integrating data from ERP/CRM/WMS systems (SAP, Oracle, legacy platforms)
Exposure to feature stores or ML training/serving consistency frameworks
Experience with IBM DataStage or legacy ETL modernization projects
Experience scaling distributed ML or time-series models in production environments
Why This Role
This is a strong fit for someone who enjoys working in complex, real-world data environments, especially with messy, high-volume retail-style data and close collaboration with ML teams. Retail or similar domains are highly valued.
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