Data Architect / Data specialist – London – Hybrid – 1 or 2 days a week in office – Azure, SQL, Data Bricks, API, data warehouses, data lakes, lake house, cubes, reporting - £100,000 - £115,000
Perfect for a Data Consultant / Engineer to take the next step in their careers
Summary of the role
My client is looking for experienced professional to lead the architecture and design of our data services and assist the group with defining and supporting wider data programmes. As the Data Architect, you will address technical business needs with innovative, efficient data solutions.
Responsibilities
Support the definition of the technical vision and strategy for the data platform
Lead effort to design and architect our data platform to support different methods to ingest and process data, presenting at review boards as necessary
Adhere to all architecture and design best practice highlighting inconsistent practices and drive consistency
Develop reusable patterns, templates and architecture artefacts to ensure project delivery is optimized
Align the architecture approach with the overall Group’s architecture strategy
Interacts with the delivery team to help to ensure successful delivery of each sprint iteration and product
Meet data and security compliance regulations as part of application design and implementation
Support the Head of Data Platform and Data Engineers in governance the platform ecosystem
Develops database and architecture documentation to share with management and implementation teams
Work with Data Architects and Specialists around the wider Group
Provide technical leadership to the Data Warehouse teams
Requirements
Experience of working as a data focused architect or similar role (at least 5 years)
Proven experience in following architecture processes for design and governance
Experience in using Azure cloud platforms, including core data services
Familiar with general IT principles (e.g. RDMS, report-building and analytic products etc.)
Experienced with data and analytic applications build processes at all stages of the software development lifecycle
A comprehensive understanding of data warehousing, extract, transform and load both at a software and hardware level
Experience in data modelling and use of modelling tools
Experienced in automating inclusion of logical data model into physical models (e.g. API specs, specifying business rules)
Highly organized, with good planning/prioritization/time management skills
Exposure and experience of data and analytics architecture (data warehouses, data lakes, lake house, cubes, reporting, RDM, MDM, etc..)
Exposure and experience Azure data and analytics products and services (sql and NoSQL databases, data lake, synapse, data bricks, PowerBI)
