We are seeking an experienced

Senior Data Modeler

with strong expertise in

enterprise data modeling and insurance/reinsurance data . The candidate will design, develop, and maintain

conceptual, logical, and physical data models

supporting analytics, reporting, actuarial, underwriting, broker, and enterprise data initiatives.

The ideal candidate will work closely with

Business Analysts, Data Analysts, Data Engineers, Data Architects, Actuaries, Underwriters, and Reporting teams

to translate business requirements into scalable data structures.

The candidate should have strong experience with

source-to-target mapping, dimensional modeling, data warehousing, data governance, metadata, and data lineage . Experience with

insurance, underwriting, reinsurance, or broker data

is highly preferred.

Experience with

Databricks and Azure data platforms

is a strong plus.

Key Responsibilities

Design and maintain

conceptual, logical, and physical data models

for enterprise data environments.

Develop scalable

enterprise, dimensional, analytical, and operational data models .

Design

star and snowflake schemas, fact and dimension tables, hierarchies, relationships, and slowly changing dimensions .

Define data grain, aggregation logic, keys, relationships, and reusable enterprise entities.

Design models supporting

data warehouses, data marts, data lakes, lakehouses, analytics, and reporting platforms .

Translate business and reporting requirements into logical and physical data structures.

Create detailed

source-to-target mappings and transformation specifications .





Work with Data Engineers and Architects to ensure models are properly implemented in ETL/ELT pipelines.

Use SQL for

data profiling, investigation, validation, relationship analysis, joins, and aggregations .

Ensure data models support

actuarial, underwriting, broker, finance, regulatory, and enterprise reporting .

Define and maintain data dictionaries, metadata, lineage, business definitions, and data standards.

Collaborate with business and technical stakeholders to establish consistent data definitions and business rules.

Ensure models comply with enterprise

data governance, security, privacy, quality, and compliance standards .

Optimize data models for large-scale analytical environments, considering

partitioning, indexing, clustering, distribution, and query performance .

Required Skills

Senior-level experience as a

Data Modeler, Enterprise Data Modeler, Data Architect, or similar role .

Robust expertise in:

Conceptual / Logical / Physical Data Modeling

Dimensional Modeling

Star / Snowflake Schema

Fact / Dimension Design

Data Grain and Aggregation

Primary / Foreign Keys

Relationships and Hierarchies

Slowly Changing Dimensions (SCD)

Master and Reference Data

Experience with

source-to-target mapping





and transformation specifications.

Experience with

ETL/ELT and data integration

concepts.

Experience with relational databases, data warehouses, data marts, and cloud data platforms.

Understanding of structured and semi-structured data.

Experience with data lineage, metadata, data catalogs, and data dictionaries.

Strong communication and stakeholder management skills.

Preferred Technical Skills

Databricks

Cloud data warehousing/lakehouse platforms

Data governance and metadata management tools

Data quality and lineage platforms

Insurance / Reinsurance Domain – Highly Preferred

Broking

Policy Administration

Premium and Commission Processing

Claims

Risk and Exposure

Actuarial Reporting

Broker Reporting

Regulatory Reporting

Candidates should understand insurance data entities such as: Policy | Risk | Insured Party | Broker | Submission | Quote | Bound Business | Premium | Commission | Claim | Exposure | Financial Transaction

Experience modeling complex

insurance and underwriting business processes , business rules, reporting requirements, and KPIs is highly desirable.

Data Governance / Metadata

Experience with enterprise

data governance and metadata management .

Understanding of:

Business & Technical Metadata

Data Ownership & Stewardship

Data Quality Rules

Critical Data Elements (CDEs)

Data Classification

Data Standards & Naming Conventions

Ability to align data models with enterprise governance, security, privacy, and compliance requirements.

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📌 Senior Data Modeler – Insurance / Reinsurance / Underwriting / Broker Reporting (Winnipeg)
🏢 Precision Technologies
📍 Winnipeg