Data Modeller

Project for a client in the financial sector.

The Team

The team consists of individuals working on global, regional, and local projects supporting all Global Businesses and Global Functions. The Data Modelling role is responsible for modelling data within specific Businesses, Functions, and/or Geographies, working with Data CIOs, Data Officers, and their teams as needed.

The Role

The Data Modeller designs, implements, and documents data architectures and data models for solutions using application, relational, dimensional, and NoSQL databases. These solutions support enterprise information management, business intelligence, operations, machine learning, data science, and other business interests.

The successful candidate will:

• Develop conceptual, logical, and physical data models.
• Oversee implementation of RDBMS, operational data stores (ODS), application databases, data marts, and data lakes on target platforms, including SQL, NoSQL, cloud, and on-premises environments.
• Govern the expansion of existing data architecture and optimise data-query performance through best practices.
• Work independently and collaboratively.

Responsibilities

• Implement business and IT data requirements through new data strategies and designs across application, relational, dimensional, and NoSQL platforms, as well as reporting, visualisation, analytics, operations, and machine-learning tools.
• Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual, logical, and physical data models.
• Define and govern data-modelling and design standards, tools, best practices, and related development for enterprise data models.
• Identify the architecture, infrastructure, and interfaces for data sources; tools supporting automated data loads; security concerns; analytical models; and data visualisations.
• Perform hands-on modelling, design, configuration, installation, performance tuning, and sandbox proof-of-concept work.
• Proactively and independently address project requirements and communicate issues and challenges to reduce delivery risks.

Requirements

• 3+ years of hands-on relational, dimensional, and/or analytical experience using RDBMS, dimensional and NoSQL data-platform technologies, ETL, and data-ingestion protocols.
• MongoDB experience is an advantage.
• Good knowledge of metadata management, data modelling, and related tools such as Erwin or Visual Paradigm.
• Experience with data warehouses, data lakes, and enterprise big-data platforms in multi-data-centre contexts is desired.
• Team-management, communication, and presentation experience.
• Strong communication skills and good spoken English.