Director – Data Architect – Gft
| Company | Royal Bank of Canada |
|---|---|
| Location | Toronto, ON, Canada |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | |
| Experience Level | Senior, Expert or higher |
Requirements
- Advanced quantitative, qualitative, analytical, problem solving, and critical thinking skills.
- Advanced knowledge of databases and engineering concepts with hands on experience with one or more data analytics/programming tools such as Hive/SQL/Spark/Python.
- Experience utilizing querying, automation, and big data technologies (e.g. Python, SQL, Spark, Teradata, Hadoop, Snowflake, Databricks) to produce repeatable insights.
- Minimum of 7+ years of analytical experience in applying solutions to business problems in relevant fields such as analytics, business consulting, or other data-driven functions.
- Exceptional storytelling skills, with a track record of translating complex data into compelling business insights. Ability to communicate findings derived from complex analytics to Senior Leadership, both verbally and visually.
- Solid understanding of Finance business processes such as Balance Sheet Reporting, Profit and Loss Reporting, Capital Reserve Reporting, Capital Markets products and processes, and Regulatory Reporting.
Responsibilities
- Lead a team of analysts within Data Engineering group, including project oversight, coaching and professional development.
- Ability to inspire highest level of quality/rigor/thought leadership in compete data lifecycle including gathering, transforming, reporting and analytics of the large data sets.
- Leverage big data and cutting-edge data mining techniques, provide thought leadership in analytic techniques and business applications to unlock the value of Bank’s unique data set.
- Lead development of assets supporting scalable analytic approaches capable of being leveraged by data scientists / analysts globally.
- Evangelize new analytic approaches for processing big data through internal training, documentation and by leading technical sharing sessions.
- Utilize Hadoop, and related query engines, such as Hive, Databricks, Snowflake, to perform advanced data mining and analysis.
- Research industry metrics and business context and bring this context to bear in analyses.
- Find opportunities to create and automate repeatable analyses or build self-service tools for business users.
- Make recommendations and build use cases on new sources of value by addressing the biggest gaps in our data sources in relation to completeness.
Preferred Qualifications
- Data Engineering / Data Science certification and/or completion of Business Analysis training courses.
- Hands on experience in Databricks / Snowflake/ Hadoop / Data lakehouse technologies.
- Expertise in the application of predictive modeling and machine learning techniques.
- Proficiency with creating compelling presentations.