Data Analyst at Wellington-Altus | CA | Rezi

Data Analyst at Wellington-Altus

Data Analyst

Wellington-Altus · CA

1 weeks ago

Data Analyst

Wellington-Altus · CA

7 days ago
Resume preview

Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now
Resume preview

Tailor your resume to this Data Analyst role.

Rezi rewrites your resume against Wellington-Altus's job description. Free.

Resume score gauge reading 58 out of 100

Don't guess if your resume is good enough.

See how it scores against the Data Analyst posting at Wellington-Altus — free, in seconds.

About the Role

We are seeking a detail-oriented and technically proficient Data Analyst with a strong foundation in capital markets and financial domain knowledge to support data analysis across the organization. The ideal candidate will have hands-on experience working with AWS-based data environments, strong SQL expertise, and the ability to translate business requirements into a functional spec.

Responsibilities

  • Analyzing and interpreting large datasets related to capital markets, portfolios, and financial transactions
  • Developing, optimizing, and maintaining SQL queries across cloud data platforms (Redshift, Athena, Postgres)
  • Collaborating with Data Engineers to support data ingestion, ELT workflows & transformations
  • Monitoring and troubleshooting data pipelines by querying CloudWatch logs
  • Supporting data validation, reconciliation, and ensuring data accuracy and integrity
  • Generating reports, dashboards, and insights for business stakeholders
  • Documenting functional requirements, data processes, pipelines, and usage guidelines

Requirements

  • Bachelor’s degree in Business, Economics, Statistics, Data Science, Information Systems, or a related discipline, or equivalent experience
  • 5+ years of experience in data analysis, including business analysis responsibilities
  • Demonstrated expertise in data mining, evaluation, analysis, and visualization
  • 2+ years of experience in the financial services industry, with exposure to wealth management and/or capital markets
  • Strong analytical, problem-solving, and business analysis skills with experience in Agile and/or Waterfall environments
  • Proven expertise in requirements management, business process analysis, and data mapping
  • Ability to bridge business and financial domain knowledge with technical and data solutions
  • Knowledge of data modeling, database design, and data validation/testing practices
  • Excellent communication, facilitation, and stakeholder management skills across technical and business audiences
  • Effective collaboration with cross-functional teams in fast-paced, cloud-based environments
  • Experience with segmentation techniques and advanced data design concepts is an asset
  • Proficiency with the MSOffice suite, including Word, Excel, Powerpoint, Teams, and Outlook
  • Experience with data pipelines and ETL processes in cloud environments
  • Familiarity with Python for data analysis or scripting
  • Experience with BI tools (e.g., Power BI, Tableau)
  • Understanding of data modeling and warehouse design
  • Exposure to Agile or data product environments
  • Advanced SQL expertise across AWS Redshift, AWS Athena, PostgreSQL
  • Hands-on experience with AWS ecosystem, including AWS Glue (jobs, configurations), AWS Lambda, AWS Secrets Manager / Parameter Store, Workflow orchestration (DAGs – e.g., Airflow or similar), CloudWatch (log querying and monitoring)
  • Must be legally eligible to work in Canada
  • A background check, satisfactory to the employer, may be required of the successful applicant prior to commencing employment

Skills

  • Data Analysis
  • Capital Markets
  • Financial Domain Knowledge
  • AWS
  • SQL
  • Data Mining
  • Data Evaluation
  • Data Visualization
  • Financial Services Industry
  • Wealth Management
  • Business Analysis
  • Agile
  • Waterfall
  • Requirements Management
  • Business Process Analysis
  • Data Mapping
  • Data Modeling
  • Database Design
  • Data Validation
  • Data Testing
  • Communication
  • Facilitation
  • Stakeholder Management
  • Cross-functional Collaboration
  • MSOffice Suite
  • Excel
  • Powerpoint
  • Teams
  • Outlook
  • Data Pipelines
  • ETL Processes
  • Python
  • BI Tools
  • Power BI
  • Tableau
  • Warehouse Design
  • AWS Glue
  • AWS Lambda
  • AWS Secrets Manager
  • Parameter Store
  • Airflow
  • CloudWatch

Location

  • Toronto, ON

Work Type

  • Full-time

Experience Level

  • 5+ years of experience in data analysis
  • 2+ years of experience in the financial services industry

Education Level

  • Bachelor’s degree in Business, Economics, Statistics, Data Science, Information Systems, or a related discipline, or equivalent experience

Salary/Compensations

  • $100,000 - $120,000 annually

Benefits

  • Health insurance
  • Accident insurance
  • Life insurance
  • Other unique benefits per location
  • Discretionary bonuses

About the Company

  • Founded in 2017, Wellington-Altus Financial Inc. (Wellington-Altus) is one of Canada’s Top Growing Companies* and the parent company to Wellington-Altus Private Counsel Inc., Wellington-Altus USA Inc., Wellington-Altus Insurance Inc., Wellington-Altus Group Solutions Inc., Independent Advisor Solutions Inc., and Wellington-Altus Private Wealth Inc.—the top-rated** investment dealer in Canada.
  • With more than $50 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.

Equal Opportunity

  • Wellington-Altus Private Wealth is strongly committed to equity and diversity within its community and welcomes applications from women, racialized persons, Indigenous peoples, persons with disabilities, and persons of all sexual orientations and genders. All qualified individuals who would contribute to the further diversification of our organization are encouraged to apply.
  • If you require accommodation for the recruitment process, please let us know at the point of application.