Data management:

• Developing and implementing plans, policies, and practices that control, protect and optimise the value of data assets;
• Devises and implements master data management processes for specific subsets of data;
• Assesses the integrity of data from multiple sources;
• Provides advice on the transformation of data from one format/medium to another;
• Maintains and implements information handling procedures;
• Enables the availability, integrity and searchability of information through the application of formal data and metadata structures and protection measures.

Programming/software development:

• Designs, codes, verifies, tests, documents, amends and refactors moderately complex programs/scripts;
• Applies agreed standards and tools to achieve a well engineered result;
• Monitors and reports on progress;
• Identifies issues related to software development activities;
• Proposes practical solutions to resolve issues;
• Collaborates in reviews of work with others as appropriate.

Data modelling and design:

• Investigates enterprise data requirements where there is some complexity and ambiguity;
• Plans own data modelling and design activities, selecting appropriate techniques and the correct level of detail for meeting assigned objectives;
• Provides advice and guidance to others using the data structures and associated components.

Data engineering:

• Designs, implements, and maintains complex data engineering solutions to acquire and prepare data;
• Creates and maintains data pipelines to connect data within and between data stores, applications and organisations.

Data science:

• Investigates the described problem and dataset to assess the usefulness of data science and analytics solutions;
• Applies a range of data science techniques and uses specialised programming languages;
• Understands and applies rules and guidelines specific to the industry, and anticipates risks and other implications of modelling;
• Selects, acquires and integrates data for analysis;
• Develops data hypotheses and methods and evaluates analytics models;
• Advises on the effectiveness of specific techniques based on project findings and comprehensive research;
• Contributes to the development, evaluation, monitoring and deployment of data science solutions.

Business intelligence:

• Supports business intelligence needs of specific management or governance processes or operational areas;
• Investigates the need for business intelligence reporting and analysis where there is some complexity and ambiguity;
• Selects and applies non-standard business intelligence tools and techniques to provide insights and aid decision-making;
• Selects, acquires and integrates data for analysis;
• Identifies opportunities to digitise and streamline operational data handling and optimise business intelligence capabilities.

Data visualisation:

• Applies a variety of visualisation techniques and designs the content and appearance of data visuals;
• Operationalises and automates activities for efficient and timely production of data visuals;
• Selects appropriate visualisation approaches from a range of applicable options;
• Contributes to exploration and experimentation in data visualisation.

User experience evaluation:

• Evaluates design options and prototypes to obtain user feedback on requirements of developing systems, products, services or devices;
• Tests the usability and accessibility of components and alternative designs;
• Administers a range of evaluations, recording data and feedback;
• Analyses evaluation data and recommends actions;
• Identifies areas for future user research;
• Checks systems, products, services or devices for adherence to applicable standards, guidelines, style guides, and legislation;
• Evaluates the usability of existing or competitor systems to provide benchmark values and as input to design.