Data Modeler

Key Responsibilities-

• Review existing domain data mart models/architecture to ensure that they meet the needs of our data strategy and are optimized to support our key analytical use cases.
• Design and develop remediated designs/models and work with engineering and analytical stakeholders across the different domains to create backlogs for model standardization and improvements.
• Ensure storage and consumption approaches/designs deliver maximum efficiency, with a focus on balancing storage and compute costs optimally.
• Produce and maintain modelling and design guardrails, standards and processes and integrate these with wider data management and engineering governance, for example:
• Data query performance
• Data table structures
• Partitioning of data across S3 and other object stores
• Data Lifecycle Management – especially in AWS S3 and other cloud object file systems where storage costs are key
• Where and how business logic is developed, tested, approved and embedded
• Who can create permanent or semi-permanent data, where it can be created and how it is managed
• How data is presented and accessed
• Review data modelling and technical approaches to ensure that they are consistent and of high quality.

Skills

• An experienced, driven expert in a broad set of data capabilities such as:
• Data design patterns and optimization across disparate mediums within a Cloud-based environment (preferably AWS) such as large object file systems (AWS S3), RDBMS and columnar databases
• A strategic thinker who can define modelling patterns for various layers of a data environment balancing storage vs. compute costs, optimized for as broad a set of use cases as possible
• Extensive data modelling experience, from conceptual to physical
• Expertise in different modelling methodologies such as 3NF, Dimensional, Data Vault
• Expertise in building cloud data warehouses using Kimball, preferably using AWS Redshift
• Knowledge/experience of building queries and MI outcomes utilizing data visualization technologies (e.g., Tableau)

• Qualifications in RDMBS design and/or administration and in AWS architecture (at least one of these)

• Awareness of data governance and data ethics in the production of automated modelling

• Proven track record of delivery of modelling designs/approaches in large scale data environments

• Evidence of broad stakeholder management from senior business level down to analyst

• Experience in or extensive exposure to MI/BI use cases, data exploration and analysis. Experience within predictive modelling/Data Science would be an advantage

• Experience in defining and delivering data monitoring across a large platform as well as establishing governance forums, processes and guardrails to ensure compliance with standards.