About the role
Description Data Modeler – Retail / Finance Domains (One‑Page JD) Role Overview Seeking an experienced Data Modeler with strong Retail (preferably Loyalty) and Finance/Capital Markets domain knowledge. The role focuses on designing scalable, consistent, and extensible data models that support complex operational lifecycles across multi‑system environments.
Key Responsibilities Data Modeling & Architecture
- Design conceptual, logical, and physical data models across Retail, Supply Chain, Banking, and Capital Markets domains.
- Model time‑series, reference, market, and transactional data.
- Align designs with Medallion Architecture (Bronze/Silver/Gold) and cloud lakehouse environments (AWS, Spark, Parquet, Iceberg).
Standards & Governance
- Define modeling standards, templates, naming conventions, and data dictionaries.
- Establish best practices to ensure consistency, scalability, and long‑term extensibility.
Model Review & Optimization
- Evaluate existing data models for alignment with best practices.
- Identify gaps, inconsistencies, and improvement areas for multi‑system integration.
Lifecycle‑Wide Modeling Support
- Setup: Introduce new attributes for segmentation, eligibility, rules, and workflow triggers.
- Execution: Model structures supporting multi‑step workflows, state transitions, and real‑time/near‑real‑time flows.
- Financial Processing: Define data required for funding logic, allocation rules, settlement, and reconciliation.
- Analytics: Build scalable facts, dimensions, and hierarchies for performance measurement and insights.
Collaboration
- Work with business SMEs, architects, engineering, finance, and analytics teams.
- Translate business rules into normalized, logical, and physical models.
Required Skills & Experience
- 6–12 years of enterprise data modeling experience in complex, multi‑system environments.
- Strong expertise in ERwin, ER/Studio, PowerDesigner, or similar tools.
- Proficient in relational, dimensional, and lakehouse modeling.
- Hands‑on experience with cloud storage formats (Parquet/Iceberg) and distributed computing platforms.
- Solid understanding of Finance & Capital Markets data (trades, risk, positions, reference data).
- Strong communication, analytical, and documentation skills.
Preferred Qualifications
- Exposure to Azure, Databricks, Snowflake, DBT.
- Knowledge of data governance, lineage, and regulatory compliance.
- Experience working in Agile/Scrum environments.
Why Ness Ness offers global, innovative projects across industries, enabling fast career growth. Employees collaborate with highly skilled professionals, work on industry‑leading platforms, and contribute to solutions built on values of rigor, innovation, and partnership.
About Ness Digital Engineering
Ness Digital Engineering, acquired by global investment firm KKR in 2022, is a full-lifecycle digital engineering firm offering digital advisory through scaled engineering services. Headquartered in New York, Ness serves our customers across 11 innovation hubs in the US, Eastern Europe, and India. Combining our core competence in engineering with the latest in digital strategy and technology, we seamlessly manage Digital Transformation journeys from strategy through execution to help businesses thrive in the digital economy. For more information, visit www.ness.com.
About the role
Description Data Modeler – Retail / Finance Domains (One‑Page JD) Role Overview Seeking an experienced Data Modeler with strong Retail (preferably Loyalty) and Finance/Capital Markets domain knowledge. The role focuses on designing scalable, consistent, and extensible data models that support complex operational lifecycles across multi‑system environments.
Key Responsibilities Data Modeling & Architecture
- Design conceptual, logical, and physical data models across Retail, Supply Chain, Banking, and Capital Markets domains.
- Model time‑series, reference, market, and transactional data.
- Align designs with Medallion Architecture (Bronze/Silver/Gold) and cloud lakehouse environments (AWS, Spark, Parquet, Iceberg).
Standards & Governance
- Define modeling standards, templates, naming conventions, and data dictionaries.
- Establish best practices to ensure consistency, scalability, and long‑term extensibility.
Model Review & Optimization
- Evaluate existing data models for alignment with best practices.
- Identify gaps, inconsistencies, and improvement areas for multi‑system integration.
Lifecycle‑Wide Modeling Support
- Setup: Introduce new attributes for segmentation, eligibility, rules, and workflow triggers.
- Execution: Model structures supporting multi‑step workflows, state transitions, and real‑time/near‑real‑time flows.
- Financial Processing: Define data required for funding logic, allocation rules, settlement, and reconciliation.
- Analytics: Build scalable facts, dimensions, and hierarchies for performance measurement and insights.
Collaboration
- Work with business SMEs, architects, engineering, finance, and analytics teams.
- Translate business rules into normalized, logical, and physical models.
Required Skills & Experience
- 6–12 years of enterprise data modeling experience in complex, multi‑system environments.
- Strong expertise in ERwin, ER/Studio, PowerDesigner, or similar tools.
- Proficient in relational, dimensional, and lakehouse modeling.
- Hands‑on experience with cloud storage formats (Parquet/Iceberg) and distributed computing platforms.
- Solid understanding of Finance & Capital Markets data (trades, risk, positions, reference data).
- Strong communication, analytical, and documentation skills.
Preferred Qualifications
- Exposure to Azure, Databricks, Snowflake, DBT.
- Knowledge of data governance, lineage, and regulatory compliance.
- Experience working in Agile/Scrum environments.
Why Ness Ness offers global, innovative projects across industries, enabling fast career growth. Employees collaborate with highly skilled professionals, work on industry‑leading platforms, and contribute to solutions built on values of rigor, innovation, and partnership.
About Ness Digital Engineering
Ness Digital Engineering, acquired by global investment firm KKR in 2022, is a full-lifecycle digital engineering firm offering digital advisory through scaled engineering services. Headquartered in New York, Ness serves our customers across 11 innovation hubs in the US, Eastern Europe, and India. Combining our core competence in engineering with the latest in digital strategy and technology, we seamlessly manage Digital Transformation journeys from strategy through execution to help businesses thrive in the digital economy. For more information, visit www.ness.com.