Data Engineer

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

Job Description

Working cross‑functionally with business managers, product managers, engineers and data scientists to gather requirements and understand their business processes. 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 to enable organization‑wide experiments, research and production deployments. Implement systems to deliver insights to business units and customers. Apply Dev‑Ops processes for production‑level delivery and maintenance. Apply quality processes to ensure requirements are met. Implement and manage security according to industry standards. Document all aspects of design, implementation, testing, and release.

Job Requirements

As a successful applicant, you would have a graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field and the ability to manage stakeholders and communicate well. You will have strong experience in cloud technologies (AWS/Azure or similar) with at least 5 years of experience in a Data Engineer role.

• A history of working with large scale reliable data systems
• Proficient with cloud technologies and native services
• Experience with big data tools and delivery of big data solutions
• Experience with different types of data stores including SQL, NoSQL, warehouses, lakes, etc.
• Experience working in Hadoop ecosystem and Spark is a plus
• Experience with data ingestion and data integration tools and frameworks, data pipeline and workflow management, common data science tools such as R, Python, Big data technologies, Tableau
• Proven ability to deliver high profile activities to tight timescales
• Proven ability to apply analytical and creative thought
• Ability and desire to learn and pick up new tools and technologies for problem solving, enhancing analysis results and accuracy, and optimizing workflow efficiency
• Independent and possess creative problem solving skills to address business problems from different perspectives
• Ability to distil and communicate results to all organisational levels
• Practice a lean agile scrum process to continuously deliver value to customers
• Proven success in contributing to a team‑oriented environment
• Ability to interact with global teams and manage the related cultural challenges
• Be able to interact with development teams to determine project requirements
• Readiness to travel globally.