Data Modeler

CGI•Dallas, TX

7h•Onsite

About The Position

We are seeking an experienced Data Modeler to join our team. In this role, you will be responsible for designing, developing, and maintaining enterprise data models that support both transactional and analytical platforms within the insurance domain. You will work closely with business stakeholders, Product Owners, Data Architects, and Engineering teams to translate complex business requirements into scalable, high-performing data solutions. The ideal candidate brings deep expertise in data modeling methodologies, relational database design, enterprise data architecture, and insurance domain processes. This role requires a strong understanding of data lifecycle management, integration patterns, and modern data platforms, along with the ability to influence data standards and best practices across the organization. This position is located at the client site in Dallas, TX.

Requirements

Bachelor's Degree (or equivalent experience) in Computer Science, Engineering, Information Systems, or a related field.
8+ years of experience in data modeling, database design, or data architecture.
Strong hands-on experience with: Relational databases (Oracle, PostgreSQL, MySQL), SQL development and performance tuning, Data modeling methodologies (Normalization, Kimball, Inmon).
Proven experience working with: Policy Administration Systems (OIPA preferred, or Guidewire/Duck Creek), Highly transactional (OLTP) environments.
Expertise in designing: Dimensional models (Star/Snowflake schemas), Normalized operational models, Canonical / enterprise data models.
Experience with data modeling tools such as Erwin, SAP PowerDesigner, Hackolade, or equivalent.
Strong understanding of: Data lifecycle (creation to consumption), Data integration patterns (ETL/ELT), Data warehousing and operational data stores (ODS).
Excellent communication skills including written, verbal, and technology illustrations.
The desire and aptitude for learning new technologies to solve problems and formulate recommendations.
A proven track record of working in reciprocal teams to deliver high quality data solutions in an agile environment.
A fearless approach to challenge the legacy design and seek opportunities to design better models and better code.
A passion for data analysis with the ability to navigate and master complex transactional and warehouse databases.
A love working with data and are confident in your SQL skills.
Technically adept in learning new technologies and architectural methodologies and adapting our practices to support frequent changes in the technical environment.
A strong interest in playing a technical data steward role and across our business and technology partners to understand and detail our data, appropriate data usages and helping [BU] derive the maximum value from its data.
The ability to take a broad view of data from creation to consumption and understand how data design patterns affect data quality and the ability of users to easily consume data.

Nice To Haves

Experience with cloud native data warehousing and data lake solutions using Snowflake is a plus.
Exposure to working with a Data Scientist team and knowledge of Feature Engineering is a plus.
Experience of database design through the full development lifecycle is a plus: from requirements to conceptual, logical and physical data model design and implementation.
Experience with Insurance Domain Modelling.
Experience with cloud-native data platforms such as Snowflake, Azure Synapse, or AWS Redshift.
Exposure data lakes and lakehouse architectures.
Familiarity with data governance frameworks, data lineage, and metadata tools.
Experience supporting Data Science / ML teams, including feature engineering concepts.
Knowledge of insurance regulatory and reporting requirements.
Experience working with large-scale enterprise data ecosystems.

Responsibilities

Design and maintain conceptual, logical, and physical data models for both transactional (OLTP) and analytical (OLAP) systems.
Develop data models aligned to insurance domains including policy lifecycle (quote, issue, servicing), coverages, premiums, billing, and claims.
Create and deliver data mapping specifications and transformation logic for large-scale reporting and integration platforms.
Define and enforce data modeling standards, naming conventions, and best practices across the organization.
Partner with Product Owners, Data Architects, Engineers, and Business stakeholders to translate requirements into robust data solutions.
Design canonical and enterprise data models to promote data consistency, reuse, and interoperability across systems.
Ensure data quality, integrity, and lineage are maintained throughout the data lifecycle.
Guide engineering teams in assembling large, complex datasets that meet functional and non-functional requirements.
Optimize data structures for performance, scalability, and maintainability.
Contribute to data governance efforts, including metadata management, lineage documentation, and stewardship.
Identify opportunities to modernize legacy data models and drive innovation in design approaches.
Support Agile delivery by actively participating in sprint planning, design reviews, and backlog refinement.