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 full-time remote position. You can work from Toronto, Ottawa or Montreal.We are seeking an experiencedData Engineerwho 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 DoDesign, build, and maintain scalable data pipelines and ETL processes for large structured and unstructured datasetsDevelop and optimize Spark-based data workflows supporting production ML systemsCollaborate closely with data scientists, ML engineers, and business stakeholdersTranslate complex business needs into scalable, production-grade data solutionsBuild feature engineering pipelines for time-series and predictive modelsEnsure data quality, governance, security, and reliability across systemsContinuously improve data architecture, performance, and scalabilityWhat You BringMin. 6+ years in data engineering or ML data pipeline developmentStrong experience with Apache Spark, PySpark, Databricks, Delta LakeAdvanced skills in Python, SQL, and AirflowDeep understanding of Medallion architecture and ETL design patternsExperience building time-series features (rolling windows, lags, trend indicators)Ability to work closely with ML teams and translate data into model-ready structuresBachelor’s or Master’s in Computer Science, Engineering, or related fieldPreferred ExperienceBackground in retail, e-commerce, or supply chain environments dealing with large, messy, high-volume datasetsExperience working directly with machine learning teams or supporting ML model developmentHands-on experience in forecasting, demand planning, or similar data-heavy business domainsExperience integrating data from ERP/CRM/WMS systems (SAP, Oracle, legacy platforms)Exposure to feature stores or ML training/serving consistency frameworksExperience with IBM DataStage or legacy ETL modernization projectsExperience scaling distributed ML or time-series models in production environmentsWhy 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.#J-18808-Ljbffr