JOB DESCRIPTION 

• Data Pipeline Infrastructure & Architecture 
  • Design and implement scalable data architectures on cloud data platforms with high availability, security, and performance 
  • Lead development of Data Lakehouse solutions 
  • Collaborate with stakeholders to understand requirements and translate them into technical specifications 
• Pipeline Development & Optimisation 
  • Build and maintain robust ETL/ELT pipelines using modern data engineering tools and frameworks 
  • Optimise data processing workflows for performance, cost-effectiveness, and reliability 
  • Implement automated data quality checks and monitoring systems to ensure data integrity 
• Data Systems Architecting & Solutioning 
  • Design and architect comprehensive cloud-native Data & AI solutions aligned with business objectives and technical requirements 
  • Lead cloud migration strategies and oversee implementation of complex multi-cloud environments 
  • Drive innovation through integration of Data & AI capabilities into HDB’s Data & AI platform product architectures 
  • Conduct technical assessments and recommend modernised approaches using cloud native technologies 
  • Maintain architectural documentation 
• Cloud Platform Operations 
  • Leverage Cloud Native Services to build and manage data infrastructure 
  • Implement infrastructure as code practices using Terraform 
  • Ensure compliance with security standards and data governance policies 
• Technical Leadership & Collaboration 
  • Mentor junior data engineers and provide technical guidance on complex challenges 
  • Participate in architectural reviews and contribute to data strategy evolution

REQUIREMENTS

• Bachelor’s degree in computer science, Information Technology, Computer Engineering, or related field 
• Minimum 3 years of relevant experience in data systems architecture, data systems integration, and data pipeline setup at production scale 
• Good understanding of cloud computing principles including infrastructure as code, containerisation, microservices architecture, cloud security frameworks, identity and access management, network architecture, and distributed systems 
• Proven ability to translate business requirements into technical solutions 
• Excellent communication skills for presenting complex concepts to diverse audiences 
• Experience with cloud security frameworks, compliance requirements, and risk management 
• Experience in data domains (e.g. DataOps, Data Lakehouse) and AI/ML Domains (e.g. MLOps, LLMOps) 
• Strong Knowledge and Hands-on experience with SQL, Python and Apache Spark  
• Hands-on experience with Apache Kafka, Airflow, or similar technologies 

Good to Have: 

• Proficiency in Amazon Web Services (AWS) services 
• Relevant cloud certifications (e.g. AWS Solutions Architect Professional, AWS Data Engineer Associate) would be an advantage 
• Experience with Data & AI cloud-native services (e.g. Amazon SageMaker Unified Studio, Amazon Quick Suite, AWS S3, AWS Glue, AWS Lake Formation, AWS Bedrock, AWS Agent Core). 
• Familiarity with serverless computing, edge computing, and IoT architectures would be an advantage. 
• Experience with machine learning operations (MLOps) and ML model deployment pipelines 
• Knowledge of data governance frameworks and metadata management tools 
• Familiarity with data visualisation tools and business intelligence platforms

HOW TO APPLY

Please send your application via email: [email protected] 

*By submitting your application to [email protected], you acknowledge that you have read, understood, and agreed to CMC Global’s REGULATIONS ON THE PROTECTION OF CANDIDATES’ PERSONAL INFORMATION.