2027 Investor Services, PEY Data Analyst (12-16 months)
Toronto, ON
Internship
Onsite
Intern
RBC Investor Services is a financial services organization within RBC's Wealth Management platform. The Data Analyst will manage data across platforms and projects, gather and analyze requirements, develop data quality frameworks, coordinate data flows, and build artificial intelligence and machine learning solutions to identify data anomalies.
Responsibilities
Collaborate with product, business development, Client Ops and digital teams on gathering data requirements
Analyze data within existing legacy data delivery channels, understand/translate business rules and define data requirements for delivering through modern tools and channels
Actively lead and engage in agile-like and business-led initiatives across a matrix environment
Leverage data to create efficiencies and reducing business/client risk
Build & enhance Data quality frameworks and operating models, which will deliver measurement, execution, monitoring, analysis and resolution support for datasets
Consult & confirm critical data elements (CDEs) with business, SME and Domain Experts for implementation of Data Quality Rules
Coordinate with data engineers to define Data flows and Data Quality measuring Points
Provide weekly updates for actively running data quality rules for Master Reference Data and share reports with Stewards
Actively manage the status of data quality rules enabled on datasets and investigate identified exceptions
Build “Artificial Intelligence & Machine Learning” solutions that can identify data anomalies within active production pipelines
Investigate and provide support for client exceptions & escalations
Qualification
Required
Working towards a Bachelor or master's degree in data management, Data Analytics, Data Science, Finance, Business Administration, Economics other related field
Strong personal skills and the ability to work effectively independently and within a team environment
Professional written and verbal communication skills
Good analytical, communication and problem solving skills
Highly organized with good attention to detail and very high level of accuracy
Ability to prioritize, handle multiple tasks under pressure and meet time-sensitive deadlines
Ability to think critically and “outside the box”
In order to be eligible for these student positions, you must either:
Bereturning backto school after the work term end-date
If you are not returning back to school (i.e.are graduating immediately after the work term), you must require the full work term as a mandatory component in order to graduate successfully
Preferred
Prior experience in the financial services industry, and strong understanding of the data lifecycle, including strong focus on data management and data quality practices
Data Management: ETL (PySpark, Apache Spark), Data Transformation, Data Pipelines, Data Integrity Distributed Computing: Hadoop, HDFS, MapReduce, Apache Spark
