Data Modeler

Role: Data Modeler

Location: Jaipur/ Bengaluru

Experience: 5+ Years

Work Mode: Onsite

Job Type: FTE

Key Responsibilities

Data Modeling & Design

Design and maintain conceptual, logical, and physical data models for enterprise data warehouses, data lakes, operational systems, and analytics platforms

Apply industry-standard modeling methodologies: Inmon, Kimball, Data Vault 2.0, or hybrid approaches based on use case

Create and manage entity-relationship diagrams (ERD), data dictionaries, metadata definitions, and lineage documentation

Optimize models for performance, scalability, data integrity, and ease of consumption by downstream users

Requirements & Collaboration

Partner with business analysts, product owners, domain SME and Data architect to gather and validate data requirements

Translate business processes, KPIs, and reporting needs into structured data designs

Facilitate modeling workshops, design reviews, and stakeholder alignment sessions

Work closely with data engineers to ensure accurate implementation of models in target platforms

Governance & Standards

Define and enforce data modeling standards, naming conventions, and best practices across teams

Support data governance initiatives: master data management (MDM), data quality rules, and privacy/compliance requirements (GDPR, CCPA, etc.)

Maintain version control and documentation for all data models using enterprise modeling tools

Technology & Implementation Support

Collaborate on ETL/ELT design, BI reporting, and data integration patterns to ensure models are implementable and maintainable

Support cloud data platforms (e.g., Snowflake, Azure Synapse, AWS Redshift, Google BigQuery, Databricks)

Advise on indexing, partitioning, and storage strategies to optimize query performance and cost

Experience

5+ years of hands-on experience in data modeling across transactional (OLTP) and analytical (OLAP) systems

Proven track record delivering models for data warehouses, data marts, or enterprise data platforms

Experience working in Agile/Scrum environments with cross-functional teams

Technical Skills

Proficiency with data modeling tools: ER/Studio, PowerDesigner, ERwin, SQLDBM, dbt, or similar

Strong SQL skills and understanding of relational database design (normalization, surrogate keys, slowly changing dimensions)

Familiarity with dimensional modeling techniques (star/snowflake schemas, conformed dimensions)

Knowledge of modern data stack concepts: data lakes, lakehouses, streaming data, and semi-structured data (JSON, Parquet)

Experience with at least one major cloud platform (Azure, AWS, or GCP)

Experience with Data Vault 2.0 modeling for agile, scalable enterprise warehouses

Familiarity with semantic layer design (e.g., for Power BI, Looker, Tableau)

Exposure to real-time data pipelines, event-driven architectures, or CDC patterns

Understanding of data security, masking, and role-based access control in multi-tenant environments

Knowledge of industry domains: IT4IT (Preferred)

Soft Skills

Excellent communication skills with ability to explain technical designs to non-technical audiences

Strong problem-solving, analytical thinking, and attention to detail

Collaborative mindset with ability to work effectively across distributed teams

Technologies

Modeling Tools

ERwin, ER/Studio, PowerDesigner, SQLDBM, dbt, Lucidchart

Databases

SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, BigQuery, Redshift

Cloud Platforms

Azure (Synapse, Data Factory), AWS (Glue, Redshift), GCP (BigQuery, Dataflow)

Data Engineering

dbt, Apache Airflow, Spark, Kafka, Fivetran, Stitch

Governance

Collibra, Alation, Azure Purview, AWS Glue Data Catalog

Visualization

Power BI, Tableau, Looker, Qlik (for model validation & consumption)

Success Metrics

Delivery of accurate, well-documented data models that reduce rework and accelerate time-to-insight

High adoption of modeling standards across data teams and projects

Improved data quality, query performance, and user satisfaction with data products

Positive feedback from engineering and business stakeholders on model clarity and usability