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Form of workJob Summary
Job Description
- Develop and maintain the automated data pipelines and infrastructure necessary to enabling the measurement of operations performance through single-source-of-truth datasets.
- Partner with business intelligence and workforce analytics teams to accelerate speed to strategic decision-making with quicker insight delivery through Data Engineering and support.
- Collaborate with business partners to understand and develop requirements for the ingestion and transformation of source-system data into meaningful and relatable performance datasets.
- Ensure sound governance and controls are in place for all data pipelines including adherence to documentation standards.
Must-have
• Excellent analytical and problem solving skills
• Demonstrated capability of leveraging SQL and Python to solve data problems
• Knowledge of data processing and experience in design, development, and implementation utilizing big data technologies - Hadoop, Spark Dataframe, Datameer, Teradata, SQL databases
• Ability to effectively communicate, verbally and in writing, technical concepts to a non-technical audience
• Comfort dealing with ambiguity and working independently.
• Good knowledge of Data Engineering principles, practices, and tools including data modelling, ETL processes, data integration, and data warehousing
• Experience in software development lifecycle and working knowledge of DevOps pipelines (GitHub, Jenkins, UCD/Helios)
• Proficiency in programming languages such as Python, Java, or Scala, and experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms.
Nice-to-have
• Major in Mathematics, Statistics, Engineering or Computer Science is preferred
• Experience automating routine reporting work
• Experience within Canadian Banking Operations
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