Data Analyst

CI Financial•Toronto, ON

22d•$55,000 - $95,000•Onsite

About The Position

At CI, we see a great place to work as one that is a safe place for everyone to have a voice, where people are empowered to take ownership over meaningful work, where there is an opportunity to grow through stretching themselves, where they can work on innovative products and projects, and where employees are supported and engaged in doing so. We are seeking experienced Data Analysts to support a large-scale data migration and integration initiative. You will be responsible for investigating existing data structures, analyzing business logic hidden in queries and reports, mapping source data to target systems, and collaborating with business stakeholders to ensure accuracy and completeness. This role is highly investigative and requires a blend of technical analysis and business communication skills. You should be comfortable navigating undocumented environments, reverse-engineering logic, and documenting findings clearly for both technical and business audiences.

Requirements

Strong SQL skills, with ability to read, analyze, and write complex queries.
Proven experience in data migration, data warehousing, or system integration projects.
Background in analyzing large datasets.
Strong data profiling, mapping, and reconciliation skills.
Excellent analytical and problem-solving abilities in ambiguous environments.
Strong communication skills to work with both technical teams and business stakeholders.
Experience creating data dictionaries, mapping documents, and gap analysis reports.
Experience with dashboard tools such as Sigma or equivalent
Experience with code repository systems – Bitbucket or Git

Nice To Haves

Experience with Snowflake or other modern cloud data platforms.
Familiarity with ETL/ELT processes and tools.
Exposure to financial services or other regulated industries

Responsibilities

Source System Analysis Investigate source systems and databases to understand data structures, relationships, and logic.
Analyze existing SQL queries, reports, and stored procedures to reverse engineer business rules.
Data Mapping & Transformation Map source fields to target model requirements.
Identify gaps, data quality issues, and transformation needs.
Work closely with data engineers to validate ETL/transformation rules.
Stakeholder Collaboration Partner with business SMEs and stakeholders to clarify definitions, logic, and requirements.
Translate technical findings into clear documentation for non-technical stakeholders.
Documentation & Knowledge Transfer Produce detailed data dictionaries, mapping documents, and gap analysis reports.
Capture undocumented business logic and processes uncovered during investigation.
Validation & Testing Support Support data validation and reconciliation efforts during development and UAT.
Assist in resolving discrepancies between source and target systems.