Senior Data Engineer - Machine Learning & Data Platforms

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

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Design, build, and maintain scalable data pipelines and ETL processes for large structured and unstructured datasets

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Develop and optimize Spark-based data workflows supporting production ML systems

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Collaborate closely with data scientists, ML engineers, and business stakeholders

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Translate complex business needs into scalable, production-grade data solutions

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Build feature engineering pipelines for time-series and predictive models

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Ensure data quality, governance, security, and reliability across systems

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Continuously improve data architecture, performance, and scalability

What You Bring

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Min. 6+ years in data engineering or ML data pipeline development

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Strong experience with Apache Spark, PySpark, Databricks, Delta Lake

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Advanced skills in Python, SQL, and Airflow

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Deep understanding of Medallion architecture and ETL design patterns

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Experience building time-series features (rolling windows, lags, trend indicators)

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Ability to work closely with ML teams and translate data into model-ready structures

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Bachelor’s or Master’s in Computer Science, Engineering, or related field

• Preferred Experience - we will highly consider candidates with below skills;

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Background in retail, e-commerce, or supply chain environments dealing with large, messy, high-volume datasets

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Experience working directly with machine learning teams or supporting ML model development

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Hands-on experience in forecasting, demand planning, or similar data-heavy business domains

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Experience integrating data from ERP/CRM/WMS systems (SAP, Oracle, legacy platforms)

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Exposure to feature stores or ML training/serving consistency frameworks

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Experience with IBM DataStage or legacy ETL modernization projects

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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.

APPLY: sasha@talenttohire.com