Senior Data Modeler

Role Overview: We are seeking a Senior Data Modeler with over 12 years of IT experience, including 8–10 years in data modeling and database design. The role involves designing and optimizing data models across transactional, analytical, and cloud environments using platforms such as SQL Server, Oracle, Snowflake, and Azure Synapse. The ideal candidate will collaborate with ETL and BI teams to ensure efficient data integration, governance, and performance tuning. This position requires strong expertise in conceptual, logical, and physical data modeling, metadata management, and modern data architecture concepts like data lakes and lakehouses.Core Technical Skills 1. Database Design & SQLStrong Expertise in SQL (DDL, DML, DCL).Deep understanding of RDBMS platforms (e.g., SQL Server, Oracle, PostgreSQL, MySQL).Experience with cloud databases such as Azure Synapse, Snowflake, Amazon Redshift etc.Knowledge of NoSQL systems (MongoDB, Cassandra) and modeling for semi-structured data (JSON, Parquet).2. Data Modeling Tools & TechniquesProficiency with any of the tools such as Lucidchart, Erwin, Toad Data Modeler.Strong command of conceptual, logical, and physical data modeling.Ability to model for OLTP (transactional) systems and OLAP (analytical/data warehouse) environments.Familiarity with dimensional modeling (star/snowflake schemas) for BI/analytics.3. ETL / Data IntegrationUnderstanding of ETL pipelines and data ingestion processes.Collaboration experience with ETL developers to align data flows with models.Familiarity with tools like Azure Data Factory, Informatica, Talend, dbt, SSIS. 4. Metadata, Data Governance & LineageExperience defining data dictionaries, business glossaries, and metadata repositories.Awareness of data quality, governance, and master data management (MDM) principles.Understanding of data lineage and impact analysis.5. Performance OptimizationKnowledge of indexing, partitioning, normalization/denormalization.Ability to optimize query performance through model design and database tuning.Analytical & Business SkillsAbility to translate business requirements into data structures.Experience working with business analysts and stakeholders to understand KPIs and reporting needs.Strong analytical mindset with attention to data accuracy and consistency.Understanding of domain data (e.g., finance, supply chain, healthcare).Cloud, Modern Data Stack & Emerging SkillsFamiliarity with modern data architectures — data lakes, lakehouses, and data mesh concepts.Exposure to data integration patterns.Exposure to data catalog tools (e.g., Collibra).Understanding of data modeling for BI/Analytics tools like Power BI, or Tableau.Knowledge of Python/SQL for data transformations is increasingly valuable.Experience with CI/CD for data models (e.g., dbt or Git-based version control).Soft SkillsExcellent communication — able to explain technical models to non-technical stakeholders.Collaboration with data engineers, analysts, and architects.Strong documentation and attention to detail.Ability to work in agile environments with iterative delivery.EducationBachelor’s or Master’s in Computer Science, Information Systems, or a related field.

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