Editing 2023-01-02 Senior Data Engineer BMO

Tags: [[tag:jd]] [[tag:BMO]] [[tag:DataEngineer]] Who We Are: BMO’s North American Commercial Banking serves clients across North America and commercial bankers are trusted advisors and partners to their clients, delivering sector and industry expertise, local presence and a full suite of commercial products and services. BMO North American Commercial Bank is looking to build out a data engineering and model ops team. What You’ll Do You'll consult with data scientists, the data and analytics teams, technology partners, business partners to create pipelines, governance and solutions that impact a variety of model ops, data and insight challenges across the North American Commercial Bank. You’ll wrap model ops and analytics in clean, repeatable, and automated processes. You’ll play a critical role in elevating business stakeholders’ confidence in our data. More specifically you will: - Locate data sources and demystify data contents - Become the expert on the data sourced and used in the ML operations - Establish robust pipelines for data used in the execution of ML and Analytics programs - Ensure production behavioral scores and business metrics values align with expectations - Identify and explain deviations in metrics proactively. Set in motion paths for resolution - Clarify key business metrics. Code and implement these metrics at scale - Prepare modeling master data sets in collaboration with data scientists - Create insights and visualizations which answer high impact business questions - Prepare model validation documentation Qualifications - Consultative approach engaging internal partners (e.g. data science, business, technology) desired - Experience impacting business transformation with data - Proven experience building data pipelines in production for advanced analytics use cases - Practical knowledge of software engineering concepts and best practices, inc. DevOps, DataOps, and MLOps - Proven ability to write clean, maintainable, scalable, and production ready code - Practical knowledge of software engineering concepts and best practices, inc. DevOps, DataOps, and MLOps - Strong proficiency with SQL and its variations among different databases - Skilled at optimizing large and complicated SQL statements - 4+ years production development experience - 6+ years of relevant work experience as a Data Operations Engineer - 6+ years of hands on experience in building production ETL/ELT solutions for large scale data pipelines - Familiarity with distributed computing frameworks (e.g. Spark, Dask), and analytics libraries (e.g. pandas, NumPy, matplotlib) - Familiarity with cloud platforms (e.g. AWS, Azure, GCP) - Degree in computer science, engineering, mathematics, or equivalent work experience

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