Job Description Job Description Key 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.
The Expertise Required
- 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)
Nice-to-Have Qualifications
- Experience with Insurance Domain Modeling.
- 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.
The Necessary Skills
- 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.
- 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.
The Value Delivered
- Key participant in helping to build a Data Driven Culture.
- Designing and delivering data mapping specifications for large reporting platforms.
- Writing and maintaining business rules using SQL logic
- Completing research to identify effective data designs, new tools and methodologies for data analysis.
- Collaborating with DBAs, architects, and subject area owners to create scalable data models.
- Gathering and incorporating feedback from Product Owners, Data Architects, and Data Engineers to aid in the design of the product.
- Guiding engineers in the best approach to assembling large, complex data sets that meet functional / non-functional business requirements.
- Being candid and honest in all discussions to ensure the best outcomes.
- Driving innovation and experimentation within the data organization.