Data Modeler_ Star schema_7+ Years_PAN India job in

Job Title: Data Modeler_ Star schema_7+ Years_PAN India

Functional Practices: Full Stack Developer

Job Type: Permanent

Contact Name: Jagrati Taneja

Contact Email: jagrati.taneja@crescendogroup.in

Job Ref: 134633

Published: about 8 hours ago

Position: Data Modeler / Data Product Specialist

Experience: 6+ Years

Location: Gurgaon / Noida / Pan India

Summary

An exciting opportunity for a Data Modeler / Data Product Specialist to work closely with business stakeholders, data product owners, architects, engineers, and analytics teams to design scalable, governed data products. The role involves conceptual, logical, and physical data modeling, data product design, data quality, metadata, lineage, semantic consistency, and collaboration across modern data platforms.

Location

Gurgaon / Noida / Pan India (Hybrid)

Your Future Employer

A leading NASDAQ-listed operations management and analytics company that helps global businesses enhance growth and profitability through advanced analytics, automation, technology platforms, consulting, and industry expertise. The organization serves diverse industries including insurance, healthcare, banking and financial services, utilities, travel, transportation, and logistics.

Responsibilities

• Partner with business stakeholders, data product owners, data architects, engineers, and analytics teams to understand business processes, data consumption needs, reporting requirements, and analytical use cases.
• Translate business and analytical requirements into scalable conceptual, logical, and physical data models supporting governed data products, self-service BI, operational reporting, and advanced analytics.
• Design domain-oriented data products by defining entities, attributes, relationships, hierarchies, grain, metric logic, business rules, and reusable certified datasets.
• Create and maintain ER diagrams, dimensional models, source-to-target mappings, data dictionaries, metadata definitions, lineage documentation, and model change logs.
• Develop modeling patterns across normalized, dimensional, data vault, and denormalized structures based on business consumption, performance, governance, and platform requirements.
• Define data product contracts, data quality expectations, acceptance criteria, ownership boundaries, refresh frequency, security requirements, and consumption-ready outputs.
• Perform data profiling and relationship analysis to validate source structures, identify quality gaps, assess cardinality, and recommend remediation actions.
• Collaborate with data engineering teams to ensure models are implemented accurately across warehouse, lakehouse, semantic, and reporting layers.
• Define and govern metric logic, KPI definitions, reusable business rules, data lineage, and traceability to ensure data products are auditable, explainable, and trusted.
• Support data quality design by specifying validation checks, reconciliation rules, anomaly thresholds, reference data controls, and exception-based monitoring requirements.
• Participate in model reviews, design walkthroughs, UAT support, defect triage, and sign-off discussions with business, architecture, governance, and engineering stakeholders.
• Work in an Agile delivery environment with product owners, scrum masters, program managers, and engineering teams to prioritize backlog items, refine user stories, and deliver iterative data product enhancements.

Requirements

• Bachelor's/master's degree in Computer Science, Engineering, Information Systems, Data Management, Operations Research, Statistics, or related analytics areas.
• Strong hands-on experience in conceptual, logical, and physical data modeling for analytics, reporting, data warehouse, lakehouse, or enterprise data platforms.
• Deep understanding of dimensional modeling, entity-relationship modeling, normalization/denormalization, hierarchies, slowly changing dimensions, fact tables, conformed dimensions, and model performance considerations.
• Strong SQL skills with experience in data profiling, source structure analysis, relationship validation, business rule testing, and supporting engineering teams during implementation.
• Experience creating data dictionaries, source-to-target mappings, business glossaries, metadata inventories, lineage documentation, metric definitions, and certified dataset specifications.
• Exposure to modern data platforms and tools such as Azure Data Lake, Databricks, Snowflake, Redshift, SQL Server, SAS, Power BI semantic models, dbt, Erwin, ER/Studio, or similar modeling and cataloging tools.
• Good understanding of data product concepts including ownership, reusable datasets, data contracts, quality SLAs, semantic consistency, governance controls, and consumption-ready design.
• Experience supporting data quality, reconciliation, UAT, model validation, and governance review processes across critical data assets.
• Exposure to Agile delivery concepts including backlog refinement, sprint planning, user story definition, acceptance criteria, and iterative product releases.
• Strong written and verbal communication skills with the ability to explain data models, definitions, lineage, and design trade-offs to business and technical stakeholders.

What is in it for you

• Work in a fast-paced and innovative analytics environment alongside experienced analytics and technology professionals.
• Gain exposure to...

Skills

Data Modeling,SQL Proficiency,Data Quality Management,Agile Methodology,Data Governance