Data Architect - AWS

You will operate at the intersection of data engineering, programme governance, and business intelligence, ensuring that data is accurate, scalable, and aligned to business outcomes. This is a greenfield programme, requiring strong ownership of architecture, delivery, and stakeholder alignment.

• Own end-to-end data architecture across Medallion layers (Bronze/Silver/Gold) on AWS
  
• Design atomic star schema data models (fact and dimension tables) across multiple business domains
  
• Define and implement aggregation and KPI layers aligned to business reporting requirements
  
• Establish data modelling standards, naming conventions, and design patterns across teams
  
• Ensure alignment with enterprise data strategy and roadmap
  
• Translate business processes into scalable and reusable data models
  
• Write and review SQL, Python, and Spark code for pipelines and transformations
  
• Build and validate data models in Snowflake or Databricks
  
• Deliver pipelines using AWS services (S3, Glue, Athena)
  
• Perform data reconciliation and validation across layers (source → curated → BI)
  
• Ensure data quality, consistency, and integrity across the pipeline
  
• Own end-to-end SDLC (requirements → design → build → test → release → operate)
  
• Lead and unblock data engineers and analysts on day-to-day delivery
  
• Identify blockers, dependencies, and risks early, and propose solutions
  
• Align delivery with programme roadmap and milestones
  
• Track execution using Jira and maintain documentation in Confluence
  
• Gather and validate requirements across multiple business domains
  
• Translate business requirements into technical designs and data models
  
• Communicate architecture decisions clearly to non-technical stakeholders
  
• Drive cross-team alignment to ensure consistent, reliable, and trusted outputs
  
  

• Minimum 10 years of experience in Data & Analytics Architecture with exposure to large-scale analytics transformation programmes
  
• Strong experience in Medallion architecture and AWS-based data platforms
  
• Advanced SQL (joins, window functions, performance tuning)
  
• Hands-on experience with Python and Apache Spark
  
• Experience with Snowflake or Databricks (data modelling, optimisation, pipelines)
  
• Strong expertise in data modelling (star schema, dimensional modelling, SCDs, normalisation)
  
• Proven experience in data reconciliation and validation across layers
  
• Strong understanding of full SDLC lifecycle
  
• Ability to quickly understand new business domains and processes
  
• Experience working with transaction-heavy domains (Finance, Supply Chain, HR, Customer, etc.)
  
• Experience working with ERP / enterprise systems (SAP, Oracle, Salesforce, etc.) is a plus
  
• Familiarity with frameworks like APQC / SCOR is a plus