Senior Data Engineer – Singapore

CMC Global Company Limited.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

CMC Global Company Limited. is seeking a seasoned Data Architect to design scalable cloud data architectures and lead multi-cloud Data & AI initiatives. The role targets building robust ETL/ELT pipelines, ensuring data quality, security, and governance across platforms.

You will collaborate with stakeholders to translate requirements into technical specs and guide architecture reviews, driving innovation in DataOps and MLOps within a production-scale environment.

Qualifications

• Bachelor’s degree in computer science, IT, or related field.
• Minimum 3 years of relevant experience in data systems architecture, data integration, and production-scale pipelines.
• Strong understanding of cloud computing incl. IaC, containers, microservices, cloud security, IAM, networks, distributed systems.
• Ability to translate business requirements into technical solutions and communicate with varied audiences.
• Experience with data domains (DataOps, Data Lakehouse) and AI/ML (MLOps, LLM Ops).
• Proficiency in SQL, Python, and Apache Spark; hands-on with Kafka and Airflow.

Responsibilities

• Design and implement scalable data architectures on cloud data platforms with high availability and security.
• Lead development of Data Lakehouse solutions and multi-cloud migrations.
• Collaborate with stakeholders to translate requirements into technical specs.
• Build and maintain robust ETL/ELT pipelines using modern tools and frameworks.
• Optimize data processing for performance, cost, and reliability; implement data quality checks.
• Architect cloud-native Data & AI solutions aligned with business goals; oversee security and governance.

Skills

SQL

Python

Apache Spark

Cloud architecture

Data pipelines

DataOps

MLOps

Multi-cloud

Education

Bachelor's degree

Tools

Terraform

Apache Kafka

Airflow

AWS/GCP/Azure

Job description

• 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
• 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
• 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
• 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 architectureswould 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