Senior Associate, Data Analyst

Capital One Capital One · Banking · Toronto, ON

This role is for a Senior Associate, Data Analyst at Capital One Canada. The primary focus is on leveraging deep SQL expertise to extract, transform, and analyze large, complex datasets for business insights, particularly in areas like fraud prevention, credit risk, and marketing. The role involves strategic stakeholder partnership, translating technical insights into actionable recommendations, and end-to-end data analysis, including data preparation and transformation. Basic qualifications include 2+ years of professional SQL experience, with preferred qualifications including experience with dbt, cloud environments (AWS), Python, Git, and Linux.

What you'd actually do

  1. Engage directly with senior stakeholders (e.g., line-of-business leads, product owners, risk management) to deeply understand business goals, challenges and decision needs. Partner with them to prioritize initiatives and refine strategies. Drive business strategy by proactively identifying, quantifying risks and translating complex analysis into compelling, concise recommendations that guide critical roadmap and decision-making processes.
  2. Draw clear business conclusions and present comprehensive insights that explain "what happened," "why it happened," "what it means" and "what we recommend doing next" (including risk mitigation or growth levers). Design and deploy rich data visualizations and craft crisp, executive-ready narratives and dashboards to empower senior leadership to make high-stakes decisions efficiently.
  3. Lead the full data analysis lifecycle, translating complex business problems into defined specifications and final implemented solutions.
  4. Apply expert-level SQL skills to efficiently transform raw data into clean, accessible datasets for yourself and other analysts.
  5. Build, automate and maintain critical business reporting and controls for processes and proactively identify and deliver process improvements for efficiency.

Skills

Required

  • SQL
  • data extraction
  • data wrangling
  • advanced analytics
  • Joins
  • Window Functions
  • CTEs
  • Aggregations
  • performance trending

Nice to have

  • Bachelor's or Master's Degree in a quantitative field
  • Data Analytics
  • Data Science
  • Computer Science
  • Engineering
  • Mathematics
  • Statistics
  • Economics
  • Finance
  • dbt
  • data transformation
  • data modeling
  • production-ready data warehouse
  • analytical skills
  • mathematical skills
  • stakeholder management
  • communication
  • negotiation
  • strategic thinking
  • influence
  • technical abilities
  • cloud environment
  • open-source programming
  • Python
  • large datasets
  • Snowflake
  • version control
  • Git/GitHub
  • cloud services
  • AWS
  • Linux

What the JD emphasized

  • deep expertise in SQL
  • thorough understanding of database structures
  • query optimization techniques
  • best practices for data governance
  • advanced technical analysis skills
  • strong business acumen
  • complex challenges
  • groundbreaking solutions
  • clear, concise and actionable strategic recommendations
  • working effectively with both technical and non-technical stakeholders
  • implement strategies and innovative solutions
  • enhance performance, mitigate risk and drive profitable growth
  • expert-level SQL skills
  • large enterprise data environments
  • complex business problems