Cloud Data Engineer

Elliott Moss Consulting; Singapore; On-site; SGD 110,000 - 170,000; Full time

Job summary

Elliott Moss Consulting in Singapore is seeking a skilled Data Engineer (Cloud) to design, build, and maintain cloud-based data analytics solutions, data platforms, and data engineering infrastructure.

You will work closely with stakeholders, technology teams, and vendors to deliver scalable and secure data solutions, including ETL/ELT pipelines and data lakes, using AWS services, Databricks, and IDMC.

Qualifications

• Minimum 5 years in data engineering, data warehousing, or advanced analytics solutions.
• Degree in Computer Science, IT, or related discipline.
• Experience with AWS, Databricks, and IDMC for data integration and governance.

Responsibilities

• Define, develop, and maintain blueprints, roadmaps, and reference architectures for data analytics infrastructure and services.
• Analyze business and technical requirements, develop solutions, and manage delivery through change processes.
• Design and implement cloud-based data analytics architectures and solutions.
• Lead data migration and modernization initiatives using AWS-native services, Databricks, and IDMC.
• Collaborate with stakeholders and system owners to understand requirements and identify architectural patterns.
• Develop and implement automation playbooks for managing and scaling cloud services, containers, and applications.
• Ensure cloud analytics solutions adhere to governance, security, and policy standards.
• Collaborate with DevOps and Data Engineering teams to design, implement, and optimize data pipelines and data lakes.
• Support vendor management and ensure delivered solutions are scalable and aligned with technical requirements.

Skills

Cloud Data Eng

SQL

Python

Databricks

AWS

IDMC

Data modeling

Spark SQL

DevOps

Stakeholder comms

Security & IAM

Education

BSc Computer Science

MSc preferred

Tools

Terraform

CloudFormation

Power BI

Tableau

Job description

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.
• 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.
• 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.
• 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.