Bengaluru, Karnataka
Job Summary

Offer SR for Navya

Data Modeller

Key Responsibilities

Assist with Schema Design : Help build, update, and maintain logical and physical data models. Any domain.
Translate Legacy Logic : Analyze existing legacy SQL queries and help map them into clean, structured dimensional models in the cloud.
Support the Canonical & Semantic Layers : Collaborate with Analytics Engineers to document and define columns, keys, and metrics within the shared transformation layer.
Maintain Data Contracts : Update YAML or schema files to ensure data products include required metadata, such as ownership, schema definitions, and automated test rules.
Document Lineage & Catalogue : Map end-to-end data lineage from source systems to final dashboards, and ensure all entries are kept up-to-date in the data product catalogue.
Apply DQ Checks : Integrate standard data quality tests (e.g., null checks, unique constraints, and data type validations) directly into the model definitions.

Required Skills & Experience

Core Data Modelling : 2–5 years of experience in data modelling, with a solid understanding of relational databases and Kimball dimensional modelling (Stars and Snowflakes).
Strong SQL : Advanced SQL skills with the ability to read, optimize, and reverse-engineer complex legacy queries.
Modern Cloud Exposure : Hands-on experience or strong working knowledge of cloud platforms like Snowflake or AWS S3/Lakehouses . Knowledge of Apache Iceberg is a strong plus.
Financial Services Exposure : Prior experience in banking, wealth management, or financial services is highly desirable.
Tooling Familiarity : Experience using data modelling tools (e.g., Erwin, Hackolade, or dbt) and version control systems (Git).
Eagerness to Learn : A proactive attitude and desire to grow your skills across modern analytics engineering, data contracts, and data streaming (Kafka).
Key Responsibilities

Key Responsibilities

Assist with Schema Design : Help build, update,



and maintain logical and physical data models. Any domain.
Translate Legacy Logic : Analyze existing legacy SQL queries and help map them into clean, structured dimensional models in the cloud.
Support the Canonical & Semantic Layers : Collaborate with Analytics Engineers to document and define columns, keys, and metrics within the shared transformation layer.
Maintain Data Contracts : Update YAML or schema files to ensure data products include required metadata, such as ownership, schema definitions, and automated test rules.
Document Lineage & Catalogue : Map end-to-end data lineage from source systems to final dashboards, and ensure all entries are kept up-to-date in the data product catalogue.
Apply DQ Checks : Integrate standard data quality tests (e.g., null checks, unique constraints, and data type validations) directly into the model definitions.
Skill Requirements

Required Skills & Experience

Core Data Modelling : 2–5 years of experience in data modelling, with a solid understanding of relational databases and Kimball dimensional modelling (Stars and Snowflakes).
Strong SQL : Advanced SQL skills with the ability to read, optimize, and reverse-engineer complex legacy queries.
Modern Cloud Exposure : Hands-on experience or strong working knowledge of cloud platforms like Snowflake or AWS S3/Lakehouses . Knowledge of Apache Iceberg is a strong plus.
Financial Services Exposure : Prior experience in banking, wealth management, or financial services is highly desirable.
Tooling Familiarity : Experience using data modelling tools (e.g., Erwin, Hackolade, or dbt) and version control systems (Git).
Eagerness to Learn : A proactive attitude and desire to grow your skills across contemporary analytics engineering, data contracts, and data streaming (Kafka).

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📌 Lead Consultant(Development) (India)
🏢 HCLTech
📍 India