AWS- Data Engineer
Posted
Summary
Recruiter-led role to build and run an end-to-end AWS data lake/lakehouse platform: designing ingestion pipelines (Glue, Lambda, Step Functions, AppFlow), batch/stream transformations with Glue and Redshift, and governance via Lake Formation, IAM, and the Glue Data Catalog. Needs 3-5 years in data engineering, SQL, Python or Scala, and hands-on AWS data services experience.
We are seeking a Data Engineer with below key requirements:
Key Responsibilities
Architecture& Design 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
Development& Deployment 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
Security& Governance Configure and enforce data security policies using AWS Lake Formation, IAM, and Secrets Manager Implement granular access controls at database, table, and column levels Ensure compliance with data classification, retention, and audit requirements Support data quality frameworks and observability monitoring
Maintenance& Operations Monitor platform health, performance, and pipeline reliability Troubleshoot and resolve data pipeline failures and data quality issues Maintain documentation for architecture decisions, pipeline configurations, and operational runbooks Continuously optimise platform performance and cost efficiency on AWS
Requirements:
Essential 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 Event Bridge, AWS App Flow, 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)
If you are interested, please apply to the job post or contact me at (HIDDEN TEXT)
Regrettably, only shortlisted candidates will be notified.
Business Registration Number: 200611680D|Licence Number: 10C5117 |EA Registration Number: R21102013
Key Responsibilities
Architecture& Design 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
Development& Deployment 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
Security& Governance Configure and enforce data security policies using AWS Lake Formation, IAM, and Secrets Manager Implement granular access controls at database, table, and column levels Ensure compliance with data classification, retention, and audit requirements Support data quality frameworks and observability monitoring
Maintenance& Operations Monitor platform health, performance, and pipeline reliability Troubleshoot and resolve data pipeline failures and data quality issues Maintain documentation for architecture decisions, pipeline configurations, and operational runbooks Continuously optimise platform performance and cost efficiency on AWS
Requirements:
Essential 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 Event Bridge, AWS App Flow, 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)
If you are interested, please apply to the job post or contact me at (HIDDEN TEXT)
Regrettably, only shortlisted candidates will be notified.
Business Registration Number: 200611680D|Licence Number: 10C5117 |EA Registration Number: R21102013