At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus. Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.
Data Modeler
Location
India
Posted
2 days ago
Salary
0
Seniority
Mid Level
Job Description
Data Modeler
Zensar
Role 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. Qualifications - 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). - Familiarity with: - AWS Glue (batch data pipelines) - Amazon Kinesis (real-time streaming) - Experience designing models for multi-source integrated data platforms. - Understanding of data consumption patterns for reporting and analytics. Requirements - Strong understanding of Insurance domain data models (Policy, Claims, Billing, Underwriting). - Exposure to enterprise data platforms in insurance organizations. - 5–10 years of experience in Data Modeling / Data Architecture. - Experience in cloud-based data platforms and modern data stack. Benefits - Inclusive workplace with equal employment opportunity (EEO) and affirmative action. - Encouragement of individuality, growth, and well-being.
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ZensarAt Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus. Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.
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• Design and build scalable, cloud-native data platforms from greenfield to production • Implement near-real-time ingestion pipelines using event-driven patterns • Define and enforce platform standards, including Data Lake / Lakehouse principles, medallion architecture, and data contracts • Refactor and optimise existing Spark and PySpark scripts for performance and maintainability • Introduce best practices for code quality, testing, and CI/CD across data pipelines • Drive adoption of AI tooling and agentic workflows within the data engineering team • Ensure data quality, observability, and reliability across all pipelines and platforms • Develop self-service tooling and microservices to simplify platform usage for other teams
• Work with one of our U.S.-based clients. • Develop and implement data pipelines using PySpark. • Collaborate with cross-functional teams including machine learning engineers, software developers, analytics engineers, and product managers. • Translate business requirements into highly available data solutions. • Maintain and improve existing data pipelines and systems.
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