Senior Data Engineer: Scalable Cloud Analytics Pipelines

MANN+HUMMEL; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

MANN+HUMMEL Singapore is seeking a senior Data Engineer to design and operate scalable cloud data platforms, collaborating across business managers, product managers, engineers and data scientists to gather requirements and understand processes.

You will build end-to-end data analytics pipelines, implement data architectures for experiments and production deployments, apply DevOps practices, and document designs and releases to ensure reliable, compliant production systems.

Qualifications

• Graduate degree in a quantitative field required.
• 5+ years as Data Engineer with cloud experience.
• Experience with large-scale data systems and data pipelines.
• Proficiency with cloud services and various data stores.
• Experience with Hadoop ecosystem and Spark is a plus.
• Strong communication and stakeholder management skills.
• Willingness to travel globally.

Responsibilities

• Gather requirements with business managers, product managers, engineers and data scientists.
• Design, develop, deploy and manage scalable cloud infrastructures.
• Design and manage end-to-end data analytics pipelines.
• Make strategic data architecture recommendations.
• Implement data science frameworks for experiments and production deployments.
• Deliver insights to business units and customers.
• Apply DevOps processes for production delivery and maintenance.
• Document all aspects of design, implementation, testing, and release.

Skills

Stakeholder management

Effective communication

Analytical thinking

Problem solving

Team collaboration

Adaptability

Education

Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field

Tools

AWS/Azure

Python

SQL/NoSQL

Spark

Hadoop

Tableau

Job description

MANN+HUMMEL Singapore is seeking a senior Data Engineer to design and operate scalable cloud data platforms, collaborating across business managers, product managers, engineers and data scientists to gather requirements and understand processes.

You will build end-to-end data analytics pipelines, implement data architectures for experiments and production deployments, apply DevOps practices, and document designs and releases to ensure reliable, compliant production systems.