Data Architect - Sheffield

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Job title: Data Architect

Location: Sheffield / London

Salary: Up to £60,000 per annum

Employment type: Full time

The person appointed will be an integral member of the Architecture Team and will be responsible for the design and

implementation of the enterprise wide data strategy, ensuring the strategy supports the current and future business needs.

The role will involve collaborating with Business and IT stakeholders at all levels to ensure the enterprise data strategy and

associated implementation is adding value to the business.

Main duties:

Develop and evolve the enterprise wide data strategy to support delivery of corporate objectives

Be a key stakeholder and advisor in all new strategic data initiatives and ensure alignment to the enterprise wide data strategy

Build a framework of principles to ensure data integrity across the business (including but not limited to ERP, CRM, BI, Data warehouse, external interfaces etc.)

Ensure that the Data Architecture strategy and roadmap is aligned to the business and technology strategies.

Build and maintain appropriate Enterprise Architecture artefacts including; Entity Relationship Models, Data dictionary, taxonomy to aid data traceability

Be an advocate of data security principles and ensure appropriate security practices are embedded in any data strategy

Be an active contributor to how the bank evolves Data Governance practices and influence the adoption of data standards

Develop key performance measures for data integration and quality

Support third party data suppliers in developing specifications that are congruent with the Enterprise data architecture

Knowledge and experience:

Proven experience in architecting and implementing Business Intelligence and Data warehouse platforms, Master data Management, data integration and OLTP database solutions.

Possess in-depth knowledge of and able to consult on various technologies.

Strong knowledge of industry best practices around data architecture in both cloud based and on prem solutions.

Strong analytical and numerical skills are essential, enabling easy interpretation and analysis of large volumes of data.

A comprehensive understanding of the principles of and best practices behind data engineering, and the supporting technologies such as RDBMS, NoSQL, Cache & In-memory stores.

Experience of architecting data solution across hybrid (cloud, on premise) data platforms.

A comprehensive understanding of data warehousing and data transformation (extract, transform and load) processes and the supporting technologies such as Amazon Glue, EMR, Azure Data Factory, Data Lake, other analytics products.

Experience implementing data solutions.