Data Modeller

The data modeler designs, implements, and documents data architectures and data models for solutions, which include the use of 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:

1. Be responsible for the development of the conceptual, logical, and physical data models, oversight of the implementation of RDBMS, operational data stores (ODS), application databases, data marts, and data lakes on target platforms (SQL/NoSQL/cloud/on-prem).
2. Contribute and understand the expansion of existing data architecture and the optimization of data query performance via best practices. The candidate must be able to work independently and collaboratively.

Responsibilities:

• Implement business and IT data requirements through new data strategies and designs across all data platforms (application, relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, operations and machine learning).
• Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models
• Contribute in and follow the published data modelling and design standards, tools, best practices, and related development for enterprise data models, to fulfil both business as well as technical requirements and expectations.
• Hands-on data modelling, design, configuration, installation, performance tuning, and sandbox POC.
• Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks, collaborating with relevant stakeholders across IT and business.

Skills:

• Strong communication skill, good oral English, and excellent stakeholder management skills.
• 3+ years of strong hands-on experience on relational, dimensional, and/or analytics (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
• Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-centre contexts required.
• Good knowledge of metadata management, data modelling, and related tools (Erwin or Visual Paradigm or others) required.
• Strong financial domain and data analysis skills with experience covering activities like requirement gathering, elicitation skills, gap analysis, data analysis, effort estimation, reviews, ability to translate the high-level functional data or business requirements into technical solution, database designing and data mapping.
• Dependable team player, having a sense of ownership and a problem solver attitude with solution-seeking approach and ability to work and adapt in a fast-paced and continuously changing environment.

Good to have:

• Experience in cloud data solutions (e.g., AWS, Azure, Google Cloud).
• Familiarity with big data technologies (e.g., Hadoop, Spark).
• Knowledge of industry models (BIAN, FSDM, BDW etc.) or experience in designing enterprise data models