Data Modeler - Leading UAE Bank

Global Software Solutions Group
United Arab Emirates
AED 50,000 - 200,000
Job description

The data modeler designs, implements, and documents data design patterns and data modeling solutions, which include the use of relational, dimensional, and NoSQL databases. These solutions support enterprise-wide data products implementation and enabling all forms of data dependent use-cases.


Key Responsibilities of Data Modeler:
  • Be responsible for Creating / Maintaining / Optimizing conceptual, logical, and physical data models, the implementation of operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL) using best practices to ensure high data quality and reduced redundancy.
  • Implement business and IT data requirements through new data strategy and designs across all data platforms (relational, dimensional, and NoSQL) and relevant data tools (reporting, visualization, analytics, and machine learning).
  • Defines and governs data modeling and design standards, tools, best practices, and related development for enterprise data models.
  • Managing the enhancements / expansion of existing data models and the optimization of data query performance via best practices.
  • Working closely with Data Domain Specialists & Data Product Owners for the understanding of Data Product level functional specifications, obtaining the business context and consumption patterns around the data.
  • Creating Structure / Schema for Target Data as per business requirements (nature of data + consumption patterns) by leveraging business context & data product functional specifications.
  • Performing Data Profiling as may be required to arrive at future proof data model design for Data Products.
  • Providing Technical Specifications to development team (Data Engineering & BI teams) as per final target schema for data (functional specifications are converted to fit into target structure).
  • Generating DDL (Create Table) Scripts using Data Modeling Tool, working with Technology Engineers to create the required database objects onto the respective database platform and maintaining the required enhancements.
  • Works proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks.
  • Working collaboratively with all involved teams and contributing to the advancement of data strategy operationalization.

Skills Required:
  • Bachelor's/Master's degree in Information Management, Computer Science, Engineering, or equivalent experience.
  • Preferred banking domain knowledge and multi-market experience.
  • Minimum 5+ years of hands-on relational, dimensional modeling, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
  • Experience and knowledge across different design patterns for Data Repositories such as Data Warehouse, Data Lake, Data Lakehouse, Data Mesh, Data Fabric and enterprise big data platforms including a full understanding of end-to-end data flow cycles.
  • Core Skills Required:
  • Expertise in data modeling principles / methods including conceptual, logical & physical Data Models.
  • Skills/Conceptual knowledge required to create optimal data models - Star & Snowflake Schemas, Data Vault Methodologies, Dimensional Modeling techniques (Slowly Changing, Fast Changing, Snapshot methodology, Degenerated dimensions etc.), Normalization & Denormalization, Surrogate Key Concepts etc.
  • Technical Skills Required:
  • Hands-on expertise on data modeling tools such as (SAP Power Designer, ERWin, ER/Studio etc.).
  • Knowledge in Industry Reference data models: IBM BFMDW, Teradata FSLDM, SAP FSDM etc.
  • Best Practice / Design Standard Skills Required:
  • Naming standards for Schemas, Data Objects & Data Attributes.
  • Identifying best fit data type & length for each data attribute as part of physical data model etc.
  • Leveraging common Master & Reference Data.
  • Ensures no redundancy in terms of data objects design based on nature of data (Master / Transactional / Reference).
  • Ensuring Data Objects are designed to provide long-term stability.
  • Robust knowledge of data, systems and querying tools like SAS/SQL and proven ability to quickly learn new systems and data environments.
  • Preferred knowledge across all key facets of Data Management (Data Warehousing, BI, Data Governance, Data Quality, Master/Reference Data Management, Data Privacy Management, Application side Data Management and External Data Assets Management etc.).
  • Preferred knowledge in HADOOP, Oracle, PostgreSQL & SAP HANA database technology platforms.
  • Preferred knowledge in interacting with Data Governance tools (Informatica AXON-EDC-DEQ).

Collaborative team player with strong stakeholder management skills, who can think creatively and strategically while building cross-functional and cross-divisional relationships.


Requirements:
Skills Required:
  • Bachelor's/Master's degree in Information Management, Computer Science, Engineering, or equivalent experience.
  • Preferred banking domain knowledge and multi-market experience.
  • 5+ years of experience in relational/dimensional modeling and analytics with RDBMS, NoSQL technologies, and ETL protocols.
  • Familiarity with design patterns such as Data Warehouse, Data Lake, and big data platforms.

Core Skills:
  • Expertise in data modeling principles including conceptual, logical, and physical data models.
  • Skills in creating optimal data models: Star & Snowflake Schemas, Data Vault, and normalization techniques.

Technical Skills:
  • Proficient with data modeling tools (e.g., SAP Power Designer, ERWin).
  • Knowledge of industry reference data models (IBM BFMDW, Teradata FSLDM).

Best Practice/Design Standards:
  • Understanding of naming standards for schemas and data attributes.
  • Ability to identify optimal data types and lengths at a physical data model level.
  • Experience in leveraging Master & Reference Data and ensuring no redundancy in design.
  • Design data objects for long-term stability.

Robust knowledge of data management, querying tools (SAS/SQL), and quick adaptability to new systems.


Preferred knowledge in Data Management areas, HADOOP, Oracle, PostgreSQL, SAP HANA, and Data Governance tools.


Collaborative team player with strong stakeholder management skills and a strategic mindset.

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