Data Modeler - Toronto
2 days ago
Job description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, AIT Global, Inc., is seeking the following. Apply via Dice todayJob Title:
Data Modeler
Location:
Toronto, ON (Hybrid 3 Days Onsite a week)
Role Overview:
Seeking an experienced Data Modeler with strong Finance/Capital Markets domain knowledge. The role focuses on designing scalable, consistent, and extensible data models that support complex operational lifecycles across multisystem environments.
Data Modeling & Architecture:
Design conceptual, logical, and physical data models across Retail, Supply Chain, Banking, and Capital Markets domains.
Model time, series, reference, market, and transactional data.
Align designs with Medallion Architecture (Bronze/Silver/Gold) and cloud lakehouse environments (AWS, Spark, Parquet, Iceberg).
Standards & Governance:
Define modeling standards, templates, naming conventions, and data dictionaries.
Establish best practices to ensure consistency, scalability, and long term extensibility.
Model Review & Optimization:
Evaluate existing data models for alignment with best practices.
Identify gaps, inconsistencies, and improvement areas for multisystem integration.
Lifecycle Wide Modeling Support:
Setup:
Introduce new attributes for segmentation, eligibility, rules, and workflow triggers.
Execution:
Model structures supporting multistep workflows, state transitions, and real time/near real time flows.
Financial Processing:
Define data required for funding logic, allocation rules, settlement, and reconciliation.
Analytics:
Build scalable facts, dimensions, and hierarchies for performance measurement and insights.
Collaboration:
Work with business SMEs, architects, engineering, finance, and analytics teams.
Translate business rules into normalized, logical, and physical models.
Required Skills & Experience:
6 12 years of enterprise data modeling experience in complex, multisystem environments.
Strong expertise in ERwin, ER/Studio, PowerDesigner, or similar tools.
Proficient in relational, dimensional, and lakehouse modeling.
Hands on experience with cloud storage formats (Parquet/Iceberg) and distributed computing platforms.
Solid understanding of Finance & Capital Markets data (trades, risk, positions, reference data).
Strong communication, analytical, and documentation skills.
Preferred Qualifications:
Exposure to Azure, Databricks, Snowflake, DBT.
Knowledge of data governance, lineage, and regulatory compliance.
Experience working in Agile/Scrum environments.
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