Job Summary :

We are looking for a detail-oriented Data Modeller - Level 1 to support the design, development, documentation, and maintenance of conceptual, logical, and physical data models for enterprise data platforms.

Key Responsibilities :

- Design and maintain conceptual, logical, and physical data models based on business and technical requirements.

- Develop relational and dimensional models, including fact tables, dimension tables, star schemas, and snowflake schemas.

- Define data entities, attributes, relationships, primary keys, foreign keys, surrogate keys, and business keys.

- Apply normalisation principles (1NF, 2NF, and 3NF) and appropriate denormalisation techniques.

- Implement Slowly Changing Dimensions (SCD Types 1, 2, and 3) to support historical data tracking.

- Support data warehouse and data mart development using established modelling methodologies such as Kimball and, where applicable, Data Vault.

- Work with data engineers to design data ingestion, incremental loading, Change Data Capture (CDC), and late-arriving data handling strategies.

- Contribute to layered data architecture, including raw, curated, and business-ready layers (Bronze, Silver, and Gold).

- Support data modelling on cloud platforms and warehouses such as Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse Analytics, or equivalent technologies.

- Assist in physical database design decisions, including partitioning, clustering, distribution, and query performance optimisation.

- Model semi-structured data, including JSON and nested or repeated data structures.

- Follow data governance, security, and privacy standards, including PII classification, column masking, and row-level access controls.

- Maintain data dictionaries, business glossaries, naming conventions, model documentation, and metadata.

- Manage model changes through version control, peer reviews, schema comparison, and impact analysis.

Required Technical Skills :

- Strong understanding of relational database concepts and SQL.

- Knowledge of conceptual, logical, and physical data modelling.

- Working knowledge of dimensional modelling, including facts, dimensions, grain, star schemas, and snowflake schemas.

- Knowledge of data warehouse architecture, data marts, ETL/ELT pipelines, and OLTP versus OLAP systems.

- Familiarity with data security, data governance, metadata management, and data lineage.

- Ability to create and maintain data models using tools such as ERwin, ER/Studio, SAP PowerDesigner, SQLDBM, Lucidchart, or draw.io.

Qualifications :

- Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.

- Relevant experience in data modelling, database development, data engineering, or data warehousing.