Data Engineer (AWS)

About the role

Design and architect the end-to-end AWS Data Lake and Lakehouse solution, including Landing Zone, Transformed Zone, and Curated/Consumption Zone layers. Define and govern data architecture standards, patterns, and best practices across the platform. Develop and deploy data ingestion pipelines, build and maintain data transformation workflows, and implement orchestration, monitoring, logging, and notification frameworks for pipeline operations. Configure and enforce data security policies, implement granular access controls, and ensure compliance with data classification, retention, and audit requirements. Monitor platform health, performance, and pipeline reliability, troubleshoot and resolve data pipeline failures, and continuously optimise platform performance and cost efficiency on AWS.

Key responsibilities

• Design and architect the end-to-end AWS Data Lake and Lakehouse solution, including Landing Zone, Transformed Zone, and Curated/Consumption Zone layers
• Define and govern data architecture standards, patterns, and best practices across the platform
• Architect reusable data ingestion pipelines supporting REST APIs, JDBC databases, S3 file uploads, and SaaS connectors (e.g. Salesforce via AWS AppFlow)
• Design data storage strategies including hot, warm, and cold storage tiers, encryption, and data lifecycle policies
• Develop and deploy data ingestion pipelines using AWS Glue, Lambda, Step Functions, EventBridge, and API Gateway
• Build and maintain data transformation workflows (batch and stream processing) using AWS Glue and Amazon Redshift
• Implement orchestration, monitoring, logging, and notification frameworks for pipeline operations
• Develop and maintain the AWS Glue Data Catalogue, including schema evolution tracking and metadata tagging
• Configure and enforce data security policies using AWS Lake Formation, IAM, and Secrets Manager
• Monitor platform health, performance, and pipeline reliability

About you

• Minimum 3 to 5 years of experience in data engineering, data architecture, or cloud infrastructure roles
• Hands-on expertise with core AWS data services: Amazon S3, AWS Glue, Amazon Redshift, AWS Lambda, Amazon Kinesis, AWS Step Functions, Amazon EventBridge, AWS AppFlow, AWS Lake Formation
• Strong proficiency in SQL and at least one scripting language (Python or Scala)
• Experience designing and implementing Data Lake or Lakehouse architectures
• Solid understanding of data governance, data cataloguing, and metadata management
• Experience with batch and streaming data processing patterns
• AWS Certified Data Engineer – Associate or AWS Certified Solutions Architect certification (or equivalent)
• Experience integrating with Tableau or similar BI visualisation tools via Amazon Redshift or S3 (preferred)
• Familiarity with MLOps frameworks and AI/ML model deployment on AWS SageMaker (preferred)
• Experience with Salesforce data integration using AWS AppFlow (preferred)