DE&A - Core - Advanced Data Engineering - Data Modeling

Job description

We are seeking a **Data Modeler** to design and implement **scalable, enterprise-grade data models** for an insurance client building a **modern cloud-based data platform** . The role focuses on structuring data across **Raw, Silver, and Gold layers** to support **batch and real-time ingestion** , enable **efficient reporting** , and drive **report rationalization initiatives** . The ideal candidate will have strong expertise in **data modeling (conceptual, logical, physical)** and experience working with **Snowflake, DBT, and modern data pipelines (AWS Glue, Amazon Kinesis)** . **Key Responsibilities** **Data Modeling & Architecture** - Design **conceptual, logical, and physical data models** aligned to business needs and insurance domain standards - Define and implement models across **medallion architecture (Raw, Silver, Gold layers)** - Create **scalable and reusable data structures** optimized for analytics and reporting **Data Transformation & Layer Design** - Collaborate with data engineering teams to implement models using **DBT** - Design transformation logic to move data across **Raw Silver Gold layers** - Ensure consistent data definitions, hierarchies, and business rules **Insurance Domain Data Structuring** - Model data for **core insurance functions** such as: - Policy - Claims - Billing - Customer / Party - Align data models with **industry standards and reporting requirements** **Data Integration Alignment** - Work closely with engineers handling: - **Batch ingestion via AWS Glue** - **Real-time streaming via Amazon Kinesis** - Ensure models support **multi-source data ingestion** and harmonization **Reporting & Rationalization Support** - Design optimized **Gold layer datasets** for reporting and self-service analytics (Power BI) - Support **report rationalization initiatives** by standardizing and consolidating data models - Enable consistent KPI definitions across reports **Data Quality & Governance** - Define data standards, naming conventions, and metadata structures - Ensure **data consistency, lineage, and traceability** across layers - Support governance, audit, and reconciliation requirements **Performance & Optimization** - Design models with a focus on **query performance and scalability** - Work with engineering teams to **optimize pipelines and data structures** - Apply best practices for **partitioning, clustering, and efficient joins** in Snowflake **Required Skills & Experience** **Core Technical Skills** - Strong expertise in: - **Data Modeling (Dimensional, 3NF, Data Vault – preferred)** - **Snowflake (schema design, performance considerations)** - **DBT (model structuring and transformation logic)** - Advanced proficiency in **SQL** - Understanding of **medallion architecture (Raw, Silver, Gold layers)** **Data Platform & Integration** - Familiarity with: - **AWS Glue (batch data pipelines)** - **Amazon Kinesis (real-time streaming)** - Experience designing models for **multi-source integrated data platforms** **Analytics & Reporting** - Understanding of **data consumption patterns for reporting and analytics** **Domain Expertise (Must)** - Strong understanding of **Insurance domain data models** (Policy, Claims, Billing, Underwriting) - Exposure to **enterprise data platforms in insurance organizations** **Experience** - 5–10 years of experience in **Data Modeling / Data Architecture** - Experience in **cloud-based data platforms and modern data stack**