Data Modeling Analyst - Toronto, Canada - Wellington-Altus Private Wealth Inc.

Wellington-Altus Private Wealth Inc.

Verified Company

Toronto, Canada

2 weeks ago

Posted by:

Sophia Lee

beBee Recruiter

Description

Data Modeling Analyst

Location:
This position will be in our Toronto or Winnipeg office.

Our organization:

Founded in 2017, Wellington-Altus Financial Inc.

(Wellington-Altus) is the parent company to Wellington-Altus Private Counsel Inc., Wellington-Altus USA Inc., Wellington-Altus Insurance Inc., Wellington-Altus Group Solutions Inc., Wellington-Altus Asset Management Inc., and Wellington-Altus Private Wealth Inc.—the top-rated* wealth advisory company in Canada and one of Canada's Best Managed Companies.

With more than $25 billion in assets under administration and offices across the country, Wellington-Altus identifies with successful, entrepreneurial advisors and portfolio managers and their high-net-worth clients.

- _Investment Executive 2023 Brokerage Report Card._

The opportunity:

Reporting to the Senior Manager, Data Analysis, the Data Modeling Analyst, will provide continuous automated and manual testing of data sets for use in internal data systems and for delivery from internal systems.

Such data sets can be in several formats, depending on supplier systems and client requirements, including JSON, XML, CSV, TXT, parquet, or RDF.

The Data Modeling Analyst will work in the data technology team with the data engineer team.

The role will involve developing central models, integration plans, lineage & DQ rules, and engineering best practices related to Data Modeling engineering with a specific focus on data quality and sustainability.

Key responsibilities include:

Designing, developing and maintaining data models to help with the quality and monitoring for data pipelines and processes.
Working closely with data engineers, data scientists and analysts to coordinate solution designs in terms of testability.
Supporting data governance and data profiling efforts to ensure data quality and proper metadata documentation for data lineage.
Creating quality metrics to evaluate data pipelines, visualizations, and dashboards.
Collaborating with data analysts and engineers to understand requirements, translate them into test cases and determine product quality goals and measurements.
Reproducing, isolating, and debugging issues; providing detailed bug reports.
Developing and enhancing the test infrastructure and continuous integration framework used across teams.
Validating data pipelines and data processing jobs that collect data from disparate systems and storing it in internal databases.
Identifying edge cases that can potentially break the data pipelines or compromise data quality or integrity.
Working closely with project managers to understand and maintain focus on their analytical needs, including identifying critical metrics and KPIs, and delivering actionable insights to relevant decisionmakers.
Proactively analyzing data to answer key questions from stakeholders.
Showcasing selfinitiated curiosity about what drives business performance; investigating and communicating areas for improvement in efficiency and productivity.
Creating and maintaining rich interactive visualizations through data interpretation and analysis, integrating various reporting components from multiple data sources.
Defining and implementing data acquisition and integration logic, selecting appropriate combination of methods and tools within defined technology stack to ensure optimal scalability and performance of the solution.
Developing and maintaining databases by acquiring data from primary and secondary sources, and building scripts that will make our data evaluation process more flexible or scalable across data sets.
Combining technical expertise and problemsolving passion to work closely with clients, turning complex ideas into endtoend solutions that transform our clients' business.
Leading, designing, developing and delivering enhancements to existing data models and quality engines that deliver business value for clients.
Looking to digitize and automate to a self service model and suite of service operations while managing the postproduction system and processes.
Conducting technical feasibility assessments and providing estimates for enhanced design and development of solutions.
Creating and maintaining repository of test cases and scenarios to validate the data outputs across the cloud and analytical platforms.
Supporting team members in challenging situations (resource / release challenges, crossteam communication).
Scheduling adhoc meetings to solve for disagreements or ambiguities to reduce risk of jeopardizing milestones and or artifacts.
Fostering an environment that emphasizes trust, open communication, creative thinking, and cohesive team effort between project stakeholders.
Understanding team strengths and weaknesses in order to improve each phase of the project lifecycle
Mentoring and helping junior team members grow.
Performing other duties as assigned.
A Bachelor's degree in Computer Science, Economics, Statistics or