Cloud Data Engineer

Job Overview We are seeking a highly skilled and motivated Data Engineer (Cloud) to join our Data, AI & Innovation team in Singapore. The successful candidate will be responsible for designing, developing, and maintaining cloud-based data analytics solutions, data platforms, and data engineering infrastructure. This role involves working closely with business stakeholders, technology teams, and vendors to deliver scalable, secure, and sustainable data solutions. Key Responsibilities Define, develop, and maintain blueprints, roadmaps, and reference architectures for data analytics infrastructure and services. Analyze business and technical requirements, develop appropriate solutions, and manage solution delivery through established change management processes. Design and implement cloud-based data analytics architectures and solutions. Lead data migration and modernization initiatives using AWS-native services, Databricks, and Informatica Data Management Cloud (IDMC). Work closely with business stakeholders and system owners to understand requirements and identify suitable architectural patterns. Develop and implement automation playbooks for managing and scaling cloud services, containers, and applications. Ensure cloud-based analytics solutions adhere to industry best practices, governance requirements, security standards, and organizational policies. Collaborate with DevOps and Data Engineering teams to design, implement, and optimize data pipelines, ETL/ELT processes, and data lakes. Support vendor management activities and ensure delivered solutions are scalable, sustainable, and aligned with technical requirements. Requirements Education & Experience Degree or Master's qualification in Computer Science, Information Technology, Computer Engineering, or a related discipline. Minimum 5 years of relevant experience in data engineering, data warehousing, big data, or advanced analytics solutions. Technical Skills Databases & Data Management Experience with databases such as Oracle, Microsoft SQL Server, MySQL, Teradata, or Databricks. Experience designing data repositories, including operational data stores, data marts, and data lakes. Strong SQL and data query skills, including SQL, NoSQL, and Spark SQL. Hands-on experience with Databricks, including Delta Lake, MLflow, and Apache Spark. Experience with Informatica Data Management Cloud (IDMC) for data integration, transformation, and data governance. Cloud Data & Analytics Strong knowledge of AWS cloud services, including AWS Glue, Amazon Redshift, Amazon S3, AWS Lambda, Amazon Kinesis, Amazon Athena, and Amazon EMR. Experience developing and optimizing ETL/ELT workflows using AWS-native services, Databricks, or IDMC. Understanding of event-driven architectures and microservices. Data Analytics & Machine Learning Experience in data modelling, including Star Schema and Snowflake Schema. Proficiency in Python or R for data transformation, analytics, and statistical computing. Experience with machine learning and AI frameworks for predictive modelling and analytics. Experience with data visualization tools such as Power BI or Tableau. DevOps & Cloud Security Experience with Infrastructure as Code (IaC) tools such as Terraform and CloudFormation. Knowledge of CI/CD practices and DevOps methodologies for data pipelines and cloud infrastructure. Understanding of Identity and Access Management (IAM), cloud security best practices, and data governance. Soft Skills Strong problem-solving and analytical skills. Ability to communicate complex technical concepts clearly to technical and non-technical stakeholders. Ability to work effectively with cross-functional teams and manage multiple stakeholders. Strong communication, collaboration, and stakeholder management skills. Knowledge of healthcare data governance and compliance is an advantage. Certifications The following certifications are preferred but not mandatory: AWS Certified Solutions Architect – Associate or Professional. Databricks Certified Data Engineer. Informatica IDMC Certification.