Adroit People Limited (UK)

Data Architect

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Architect in London, UK, with a contract length of unspecified duration. It offers a hybrid work model, requiring 3 days onsite weekly. Key skills include SQL, NoSQL, ETL, data governance, and data quality tools.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
November 27, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Data Quality #NoSQL #Data Lifecycle #Schema Design #Data Integration #Data Profiling #Databases #"ETL (Extract #Transform #Load)" #Data Catalog #Data Governance #Data Engineering #Data Pipeline #Data Cleansing #Data Architecture #Cloud #Data Analysis #SQL (Structured Query Language) #Dimensional Modelling #Database Management
Role description
Greetings We are Hiring Data Architect Position in London, UK Hybrid Model London, UK 3 days onsite per week JD is below: Responsible for designing and implementing Aviva target data architecture, working closely with business stakeholders, data analysts, and data engineers to understand the data requirements and objectives, and to design data models, schemas, and policies that meet those needs. The role holder will have the following technical data skills: Ability to use data modelling techniques such as entity-relationship diagrams, dimensional modelling, and schema design to represent data structures and relationships in a logical and conceptual way. Data governance tools like data catalogues, dictionaries, lineages, and policies in order to define and enforce the rules for managing the data lifecycle and usage. Proficiency in: Database management systems like SQL, NoSQL, or cloud-based databases to store, query, and manipulate data in a structured and consistent way; Data integration tools like ETL (extract, transform, load), ELT (extract, load, transform), or data pipelines for moving, transforming, and combining data from different sources and formats. Data quality tools such as data profiling, data cleansing, data validation, and data auditing for ensuring that the data is accurate, complete, consistent, and relevant; and data governance tools like data catalogues, dictionaries, lineages, and policies in order to define and enforce the rules for managing the data lifecycle and usage.