Requirements
Must have:
- 2 to 5 years of relevant experience along with appropriate IT education and/or certifications - Practical experience in ETL/ELT development/testing and data warehousing concepts - Proficient in SQL, NoSQL, Python, Spark/PySpark, and Scala - Hands-on familiarity with SSIS, Glue, cloud services (e.g., AWS, Azure), Hadoop, and Netezza - Experience handling structured, semi-structured, and unstructured datasets in both batch and streaming formats - Knowledge in data analysis, data modeling, data mapping, and data profiling
Responsibilities:
- Engage in the planning, design, development, testing, implementation, documentation, and support of data and AI products - Collaborate with business stakeholders to convert business requirements (both functional and non-functional) into effective data and AI solutions - Provide insights on technical designs and ensure they meet organizational standards and roadmaps - Enhance development efficiency by creating frameworks, automation scripts, and reusable code - Identify, monitor, and conduct regression testing on found defects - Resolve production issues, including conducting thorough root-cause analyses - Participate in initiatives for process improvements to enhance delivery and deployment capabilities
Company:
At BMO, we are part of the Data and AI Technology (DAT) Engineering team that supports our banks commitment to a Digital-First approach, focusing on risk management and compliance by developing data and AI products that yield timely, actionable insights. We pride ourselves on our diverse organization and the myriad opportunities available to apply unique skills towards solving intricate business challenges. We invest in our team members by providing a supportive environment where learning and innovation are emphasized. Our competitive salary package, comprehensive benefits, and commitment to professional growth reflect our values in fostering an inclusive workplace.
BMO Financial