Information Architect / Data Scientist
This position works in a collaborative manner with the Lead Design Authority (‘LDA’) to identify data requirements and design solutions in a manner that leverages firmwide design patterns and adheres to firmwide (data)| standards. This person is responsible for providing leadership within a technology product or business area by working in consultation with the Chief Data Office ‘CDO’ who apply data governance over business critical data .The CDO also partner with the information architect to develop the longer term strategy for data that meets business and regulatory requirements.
The Information Architect is responsible for co-developing and implementing the data strategy with the CDO, business partners and other technology leads for the data subject area domains they are responsible for. This will involve helping to develop and implement the long term systems architecture such as rationalisation of databases, identification of Systems Of Record (‘SOR’) and overseeing the population of the Asset & Wealth Management Authoritative Data Store (‘ADS’) .They will own or interact with application development (‘AD’) teams to advise and provide support in areas such as data modelling, metadata management, data quality assessment, data inventory management, data lineage and assessment of data solutions against firmwide policies and standards.
The IA will need to work with the Chief Information Architect (‘CIA’), Lead Design Authorities and other Information architects to ensure data principles and standards are upheld. They will assist project teams with the development of many types of business information models that include logical data models, physical models, interface models, object models, entity state models and physical models describing data flows. They are also responsible for the delivery of other artefacts such as Data Requirements Documents and Data Sourcing Contracts. They will assist with data analysis associated with onboarding applications to consume data form the AWM ADS. Interactions with other Information architects in other LoBs is expected and encouraged. The following extract is taken from the role of the IA as defined at a firmwide level.
· Co-ordinates with provider and consumer Domain Steward(s) to link business content (data definitions, data lineage, data quality) to technical content (data element, data model)
· Works with the Domain Steward(s) to determine authoritative data sources within the data supply chain
· Collaborates with the Domain Steward(s) to remediate the root cause of data issues
· Assists in the data management initiatives by coordinating with Domain Executive(s) and Technology and Operational Manager(s)
· Designs and facilitates the end-to-end Information Architecture (e.g. data flows, taxonomies, data models, design patterns)
· Assists Domain Steward(s) with documenting end-to-end data flow to show data lineage
· Facilitates the integration of data sets by collaborating with the Domain Steward(s)
· Provides guidance on the required infrastructure (e.g. tools, software, hardware etc.)
· Monitors data initiatives to ensure compliance with data management policy and standards
· Provides thought leadership and guidance to data framework and design considerations
· Translates data quality rules into technical rules
Detailed Job functions
· Contribute to Asset Management data architecture principles and standards. Then ensure these principles and standards are adopted in projects.
· Maintain up to date metadata. At the core of the strategic data platform is the Meta Data Repository (MDR). A key function will be management of the contents they are responsible for in the MDR. This will involve loading data models, data flow lineage, data quality metrics and other data artefacts such as data sourcing contracts. The MDR also contains the entire AWM data store inventory and it is the responsibility of the Information Architect to manage this inventory. For production data stores they need to assign the appropriate JPM Record class codes to ensure data is retained and disposed of according to firmwide policy and standards.
Owning Data Quality. Make sure the application of business data validation rules are understood by producers and consumers of data. Help data stewards with the enrichment of data models with validation rules and help provide the reporting context for data quality metrics. The IA needs to make sure data validation rules are also exposed to developers who are responsible for data entry solutions.
· Owning Data Quality. Make sure the application of business data validation rules are understood by producers and consumers of data. Help data stewards with the enrichment of data models with validation rules and help provide the reporting context for data quality metrics. The IA needs to make sure data validation rules are also exposed to developers who are responsible for data entry solutions.
· Logical Data Modelling. Work with the CDO stewards, business people and other AWM technologists to shape and define enterprise level data architecture. This will involve maintaining a conceptual model of the business domain and the development of application logical models for key subject areas. These application logical models will need to map attributes to firmwide business terms and they need to map entities to the firmwide subject area taxonomy. Models will need to be version controlled, adhere to AWM standards and be signed off by the CDO. Application logical models should be linked to the master Asset & Wealth Management logical model. In this role the data architect will need good communication (listening) and influencing skills to ensure project teams develop the proposed solution in a manner that is consistent with the agreed model and data standards.
· Physical Data Modelling. Construction of physical data models for data stores, service interfaces and data flows. The modelling process with include the skills required to optimise the design for the use cases it has to support. Ideally the modelling process should be self policing to demonstrate the model is up to date and reflects what has been deployed into the real world. Physical models need to be mapped back to the application logical model to inherit the properties of the LDM such as data confidentiality and business term descriptions.
· Generation of key data related deliverables associated with the firmwide Software Development Life Cycle such as Data Requirements Document and Data Sourcing Contract. For the applications and associated data stores they are responsible for they need to ensure compliance with firmwide standards and assist the application owner to evidence compliance.
· Participation in a number of data working groups, e.g. AWM Information Architecture Forum and GTI Data Management Technologies. Part of this responsibility will be to represent AWM communicate key messages from these working groups back to the broader AWM IA community and to escalate any issues that may prove challenging for our line of business.
· Presentation of data architecture strategies for peer review. Review and sign off data related designs for projects. This includes the development and publication of any SDLC mandated artefacts such as a Data Requirements Document and a Data Sourcing Contract that describes the data an application requires and publishes to other applications.
· Development of skills in data analytics and data science. As this is a growing area it requires an enquiring mind that wants to learn about technologies such as Natural Language Processing and to understand the benefits of R and Python. This includes finding ways of presenting information in the most appropriate format using different visualization tools.
· Train, coach, and mentor information architecture / data science skills. In some cases this will involve the generation of training material and well as the development of technology primers to help educate others with some practical lessons.
· Work with people from AD teams and the Chief Development Office to look at ways of making a data driven development process something that is a win win for developers and information architects.
Computer Science Graduate proffered, alternative Physics or Maths
Background of SW development experience
Followed by extensive related experience where the applicant has taken the principle role in data architecture Responsible for data decisions for large scale projects (excess of $1mm)
Data architecture skills, to include logical and physical data modelling
An understanding of Relational database (set) theory
Good communicator, good listener and comfortable doing presentations at board level
Relationship building, team player
Knowledge of messaging principles and data distribution architectures
Financial business knowledge 2 out of the following would be an advantage
Equity 2. Fixed Income 3. Alternatives 4. Fund Distribution 5. Transfer Agency
Construction of a business case to support a technology driven initiative
Data modelling to a competent level to be able to coach others in requirements capture
Data mining , data transfer and data profiling technologies
Data/Micro service design
Project management and estimating
Knowledge of a commercial Enterprise architecture framework
People Management skills
An understanding of Graph (RDF) theory
Data science skills e.g. data visualisation, statistics, R, Python
Meta Data Repository usage and associated tools