Data Architect - Hybrid Working

We are currently working in partnership with one of our biggest Financial Services clients. They are looking to hire an experienced Data Architect to join the ever expanding team. The role also benefits from hybrid working.

Job Role

We require a Data Architect in an enterprise-wide role. Key duties involve supporting overall IT architectural governance, helping to define & drive the data strategy, and provide technical leadership regarding reference architecture & data principles.

A regular part of the working day will involve project-level work: collaborating with both business and technical colleagues to create high level design documents.

This data architect is required to oversee both the operational & analytical data design aspects of key strategic deliverables.

Main Responsibilities as Data Architect:

• Provide thought leadership in EDS.
• Support the Senior Data Architect in driving the enterprise data strategy.
• Continual improvement of the enterprise data principles and blueprint designs.
• Participate in Solution Architecture Forum, helping to govern design or other projects and presenting own work for approval.
• Deputise for Senior Data Architect when required.
• Collaborate with squads/projects on overall solution design.
• Design and govern Central Data Platform data pipeline patterns.
• High-level ETL design/review.
• Collaborate on conceptual Datamodelling with EDS data modellers
• Present designs to relevant governance forums as required.
• Participate relevant project ceremonies such as kick-off meetings and sprint reviews
• Co-ordinate and collaborate with other teams in IT - particularly Business Architecture, System Architecture, and InfoSec
• Ensure that data management best practices are adhered to, in the areas of data security, data governance, data privacy and industry regulatory compliance

Skills and experience required:

• Insurance/financial services domain knowledge.
• Expertise in at least two of these key technologies: Azure, Azure Data Lake, Databricks, Matillion, Snowflake and Power BI.
• Event-driven architecture, including Lambda.
• Analytical system data architecture and ETL design experience.
• Hands on experience in designing and implementing a data warehouse.
• Sound understanding of dimensional Datamodelling.
• Sound understanding of metadata management, information security and GDPR.
• Understanding of SQL and Python.
• Understanding of data science and machine learning principles.
• Sound understanding of data analysis, BI and data visualisation principles.
• TOGAF knowledge a desirable benefit.

Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted.

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