Analytics engineer

You can:

• show an awareness of the need to translate technical concepts into non-technical language
• understand what communication is required with internal and external stakeholders

You can:

• interpret data to find key insights

You can:

• show an awareness of opportunities for innovation with new tools and uses of data

You can:

• show an awareness of different data models and tools, and understand when they could be used
• show an awareness of industry-recognised data modelling patterns and standards

You can:

• explain what metadata is
• maintain the information stored in metadata repositories under the direction of others

You can:

• explain the types of problems in databases, data processes, data products and services

You can:

• correctly execute test scripts under supervision
• understand the role of testing and how it works

You can:

• contribute to the design of data architecture under the direction of others

You can:

• communicate effectively with technical and non-technical stakeholders
• support and host discussions within a multidisciplinary team, with potentially difficult dynamics
• be an advocate for the team externally, and can manage differing perspectives

You can:

• undertake data profiling and source system analysis
• present clear insights to colleagues to support the end use of the data

You can:

• show an awareness of opportunities for innovation with new tools and uses of data

You can:

• produce data models and understand where to use different types of data models
• understand different tools and can compare different data models
• reverse-engineer a data model from a live system
• understand industry-recognised data modelling patterns and standards

You can:

• use metadata repositories to complete complex tasks such as data and systems integration impact analysis
• maintain a metadata repository to ensure information remains accurate and up to date

You can:

• explain the types of problems in databases, data processes, data products and services

You can:

• design, code, test, correct and document simple programs or scripts under the direction of others

You can:

• correctly execute test scripts under supervision
• understand the role of testing and how it works

You can:

• design data architecture by dealing with specific business problems and aligning it to enterprise-wide standards and principles
• work within the context of well understood architecture, and identify appropriate patterns

You can:

• communicate effectively with technical and non-technical stakeholders
• support and host discussions within a multidisciplinary team, with potentially difficult dynamics
• be an advocate for the team externally, and can manage differing perspectives

You can:

• undertake data profiling and source system analysis
• present clear insights to colleagues to support the end use of the data

You can:

• understand the impact on the organisation of emerging trends in data tools, analysis techniques and data usage

You can:

• build and review complex data models, ensuring adherence to standards
• use data integration tools and languages to integrate and store data, and advise teams on best practice
• ensure data for analysis meets data quality standards and is interoperable with other data sets, enabling reuse
• work with other data professionals to improve modelling and integration patterns and standards

You can:

• design an appropriate metadata repository
• suggest changes to improve current metadata repositories
• understand a range of tools for storing and working with metadata
• advise less experienced members of the team about metadata management

You can:

• respond to problems in databases, data processes, data products and services as they occur
• initiate actions, monitor services and identify trends to resolve problems
• determine the appropriate remedy and assist with its implementation, and with preventative measures

You can:

• use agreed standards and tools to design, code, test, correct and document moderate-to-complex programs and scripts from agreed specifications and subsequent iterations
• collaborate with others to review specifications where appropriate

You can:

• review requirements and specifications, and define test conditions
• identify issues and risks associated with work
• analyse and report test activities and results

You can:

• design data architecture that deals with problems spanning different business areas
• identify links between problems to devise common solutions
• work across multiple subject areas, or a single large or complicated subject area
• produce appropriate patterns

You can:

• listen to the needs of technical and business stakeholders, and interpret them
• effectively manage stakeholder expectations
• manage active and reactive communication
• support or host difficult discussions within the team or with diverse senior stakeholders

You can:

• understand and help teams to apply a range of techniques for data profiling
• source system analysis from a complex single source
• bring multiple data sources together in a conformed model for analysis

You can:

• identify areas of innovation in data tools and techniques, and recognise appropriate timing for adoption

You can:

• build and review complex data models, ensuring adherence to standards
• use data integration tools and languages to integrate and store data, and advise teams on best practice
• ensure data for analysis meets data quality standards and is interoperable with other data sets, enabling reuse
• work with other data professionals to improve modelling and integration patterns and standards

You can:

• design an appropriate metadata repository
• suggest changes to improve current metadata repositories
• understand a range of tools for storing and working with metadata
• advise less experienced members of the team about metadata management

You can:

• ensure that the most appropriate actions are taken to resolve problems as they occur
• co-ordinate teams to resolve problems and to implement solutions and preventative measures

You can:

• use agreed standards and tools to design, code, test, correct and document moderate-to-complex programs and scripts from agreed specifications and subsequent iterations
• collaborate with others to review specifications where appropriate

You can:

• review requirements and specifications, and define test conditions
• identify issues and risks associated with work
• analyse and report test activities and results

You can:

• design data architecture that deals with problems spanning different business areas
• identify links between problems to devise common solutions
• work across multiple subject areas, or a single large or complicated subject area
• produce appropriate patterns

You can:

• mediate between people and mend relationships, communicating with stakeholders at all levels
• manage stakeholder expectations and moderate discussions about high risk and complexity, even within constrained timescales
• speak on behalf of and represent the community to large audiences inside and outside of government

You can:

• understand and help teams to apply a range of techniques for data profiling
• source system analysis from a complex single source
• bring multiple data sources together in a conformed model for analysis

You can:

• investigate emerging trends in data-related approaches, perform horizon-scanning for the organisation and introduce innovative ways of working

You can:

• understand different ways to model data to maximise its use and value
• ensure data is modelled appropriately, and modelling standards exist and are complied with
• understand a number of data integration tools and patterns, and ensure your teams have the support and training needed to use the most appropriate methods
• build relationships with other senior data professionals (in fields such as data architecture, data engineering and data science) to share best practice and continually improve data modelling and integration processes and standards

You can:

• identify how metadata repositories can support different areas of the organisation
• communicate the value of metadata repositories
• set up robust governance processes to keep repositories up to date

You can:

• anticipate problems and know how to prevent them
• understand how problems fit into the bigger picture
• identify and describe problems, and help others to describe them
• build problem-solving capabilities in others

You can:

• set local or team-based standards for programming tools and techniques and can select appropriate development methods
• advise on the application of standards and methods and ensure compliance
• take technical responsibility for all stages and iterations in a software development project, providing method-specific technical advice and guidance to project stakeholders

You can:

• review requirements and specifications, and define test conditions
• identify issues and risks associated with work
• analyse and report test activities and results

You can:

• design data architecture that deals with problems across the enterprise
• work across all organisational subject areas and internal and external programmes

Communicating between the technical and non-technical

Data analysis and synthesis

Data innovation

Metadata management

Problem resolution (data)

Testing

Programming and build (data engineering)

Communicating between the technical and non-technical

Data analysis and synthesis

Data innovation

Metadata management

Turning business problems into data design

Communicating between the technical and non-technical

Data innovation

Testing

Testing