Data Modeler – AWS Data Platform

Dicetek LLC; Dubai; On-site; AED 180,000 - 240,000; Full time

Job summary

Dicetek LLC seeks an experienced data modeller to design scalable models on AWS (Redshift, S3) for analytics and operations. You will translate business requirements into clear logical and physical models, ensuring data integrity and performance.

You will build data dictionaries and metadata repositories, collaborating with data engineers, analysts and business stakeholders to govern data assets across the platform.

Qualifications

• Minimum 5 yrs in data modelling and data warehousing.
• Experience creating enterprise-scale data models.
• Solid SQL skills and ability to transform source data into target models.
• Knowledge of banking data domains is advantageous.
• Experience in cloud data technologies (AWS) is preferred.

Responsibilities

• Design robust scalable data models in AWS (Redshift, S3) for analytics and operations.
• Translate business requirements into logical and physical models with integrity and performance.
• Develop data dictionaries, glossaries and metadata repositories for governance.
• Collaborate with data engineers, analysts and stakeholders on data sources and transformations.
• Support data quality, lineage and governance across platforms.

Skills

Data modelling

Data warehousing

SQL

Dimensional modelling

Relational design

ETL/Transformations

Cloud data technologies

Communication with stakeholders

Tools

Amazon S3

Amazon Redshift

AWS Glue / Glue Catalog

Amazon Athena

Apache Iceberg

Job description

Design and implement robust scalable and performant data models within AWS services like Redshift RDS and S3 to support diverse analytical and operational needs

Translate complex business requirements into logical and physical data models ensuring data integrity consistency and optimal query performance

Develop and maintain data dictionaries business glossaries and metadata repositories to ensure clear understanding and governance of data assets

Collaborate with data engineers analysts and business stakeholders to understand data sources transformations and consumption patterns

Years of Experience

* Minimum 5 yrs

Required Skills

• Strong hands-on experience in enterprise data modelling.
• Demonstrable experience developing:Conceptual data modelsLogical data modelsPhysical data models
• Strong knowledge of dimensional modelling, including:Facts and dimensionsStar schemasSnowflake schemasSlowly Changing Dimensions
• Strong understanding of relational data modelling and database design principles.
• Strong SQL skills and the ability to analyse complex source data and existing database structures.
• Experience developing source-to-target mappings and transformation rules.
• Strong understanding of:Data warehousingData lakes / lakehousesMetadata managementData lineageData qualityReference and master data concepts
• Experience modelling data for analytical, reporting and downstream consumption requirements.
• Good understanding of modern cloud data technologies, preferably:Amazon S3Amazon RedshiftAWS Glue / Glue CatalogAmazon AthenaApache Iceberg
• Experience working with structured and semi-structured datasets.
• Strong analytical skills with the ability to understand complex business concepts and translate them into clear data structures.
• Ability to communicate data models and definitions effectively to both business and technical stakeholders.

Required Experience / Knowledge Areas

• Strong experience in Data Modelling, Data Warehousing and Enterprise Data Platforms.
• Demonstrable experience developing enterprise-scale data models within complex organisations.
• Experience working alongside Data Architects, Data Engineers, Business Analysts and business stakeholders.
• Experience within Banking or Financial Services strongly preferred.
• Knowledge of banking data domains such as Customer, Account, Product, Transaction, Finance, Risk and Treasury would be advantageous.
• Good understanding of enterprise data governance and data-management principles.
• Experience supporting the full development lifecycle from requirements and source analysis through modelling, engineering implementation, validation and production delivery.

Skills

data modellingdata warehousingSQL