Data Engineer

Purpose

Contributes to the overall success of the development of critical data assets/data models serving International Banking Analytics. The Data Engineer will be responsible for architecting, designing, and implementing data pipelines and data bases to be consumed for business intelligence and advanced analytics applications. Ensures all activities conducted are following governing regulations, internal policies and procedures.

Accountabilities

• Champions a customer focused culture to deepen client relationships and leverage broader Bank relationships, systems and knowledge.
• Functions as member of an agile team and helps drive consistent development practices, tools usage, common components, and patterns.
• Collaborates with analytics and business teams to build and improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization.
• Direct the identification and recommendation of appropriate solutions.
• Performs hands-on design and development with PySpark/Pandas/SQL, Parquet files, Warehousing experience preferably with object storages and Airflow scheduling / orchestration
• Spends significant amount of time writing code and testing.
• Works with the team to optimize code execution.
• Skilled with dimensional modeling and devops processes
• Understand how the Bank’s risk appetite and risk culture should be considered in day-to-day activities and decisions.
• Actively pursues effective and efficient operations of his/her respective areas in accordance with Scotiabank’s Values, its Code of Conduct and the Global Sales Principles, while ensuring the adequacy, adherence to and effectiveness of day-to-day business controls to meet obligations with respect to operational, compliance, AML/ATF/sanctions and conduct risk.
• Champions a high-performance environment and contributes to an inclusive work environment.

Education / Experience

• 2-5+ years experience working as a Data Engineer or Technical Business Analyst.
• Bachelor’s degree in Computer Science or Engineering, or related field or relevant experience.
• Strong proficiency in SQL, Python.
• Data modelling and warehousing experience would be a plus.
• Knowledge with relational databases (Oracle, DB2, Redshift, etc)
• Knowledge with JSON, Hadoop and Hive data structures would be a plus

Assets

• Experience with Big Data and Cloud Technologies (Hadoop, MinIO,Presto/Trino, Juipter Hub, AirFlow).
• API development experience.
• Experience working in Retail/Risk Banking Domain.
• Experience working in an Agile team environment.