Senior Data Platform Engineer

Visa Hunt; Singapore; On-site; SGD 74,000 - 123,000; Part time

Benefits offered by this job

AWS

Job summary

Visa Hunt in Singapore seeks a Senior Data Platform Engineer to design, build, and own scalable data platforms and production-grade data systems. You will take end-to-end ownership of data pipelines and architecture while collaborating with software engineers and stakeholders to support operational, analytical, and AI-driven use cases.

Key responsibilities include delivering end-to-end data pipelines, designing scalable data models and storage architectures, and implementing data quality,

Qualifications

• 5–7+ years of professional software engineering/data engineering experience with ownership of production data systems.
• Strong knowledge of data engineering fundamentals including ETL/ELT pipelines, data modelling, and batch/streaming architectures.
• Proficiency in Python, Java, Scala, or Go for production-grade backend applications.

Responsibilities

• Own end-to-end design, development and delivery of data pipelines and platforms.
• Design scalable data models, storage solutions and architectures for operational and analytical workloads.
• Build and maintain infrastructure for data quality, observability, monitoring and governance.

Skills

Data engineering

ETL/ELT pipelines

Python

Java

Scala

Go

Cloud data platforms

Databricks

Tools

Databricks

Unity Catalog

Delta Lake

Job description

We are looking for an experienced Senior Data Platform Engineer to design, build, and own scalable data platforms and production-grade data systems. You will take end-to-end ownership of data pipelines and architecture while working closely with software engineers and stakeholders to support operational, analytical, and future AI-driven use cases.

• Working Hours: Mon-Fri
• Working Location: Central
• Job Type: Contract
• Salary Package: Up to $11,000 (basic) + AWS

Key Responsibilities

• Own the end-to-end design, development and delivery of data pipelines, covering data ingestion, transformation, processing and serving.
• Design scalable data models, storage solutions and architectures supporting both operational and analytical workloads.
• Build and maintain frameworks and infrastructure for data quality, observability, monitoring and governance.
• Develop reliable, production-grade data systems with a strong focus on scalability, maintainability and performance.
• Contribute to overall product, data and platform architecture, collaborating with software engineers across different areas as priorities evolve.
• Design extensible data platforms capable of supporting future AI/ML and retrieval-based applications, including RAG use cases.
• Play a key role in technical architecture and engineering decisions, identifying and communicating technical trade-offs and risks.
• Collaborate with technical and business stakeholders on platform architecture, infrastructure and deployment decisions.
• Ensure appropriate handling of sensitive data, security requirements and system constraints within a regulated environment.
• Apply sound software engineering practices across system design, APIs, testing, deployment and production support.

Requirements

• 5–7+ years of professional software engineering/data engineering experience, with demonstrated ownership of production data systems from design through deployment and operations.
• Strong knowledge of data engineering fundamentals, including ETL/ELT pipelines, data modelling, batch processing and streaming architectures.
• Strong proficiency in at least one general-purpose programming language such as Python, Java, Scala, Go or equivalent.
• Proven experience developing production-grade backend applications or systems, beyond standalone data scripts and pipelines.
• Good understanding of software engineering principles, including API design, system architecture, testing and maintainable code.
• Hands-on experience with cloud-native data platforms, modern data architectures or lakehouse solutions.
• Ability to work independently, take ownership of complex technical areas and contribute significantly to architectural decisions.
• Strong analytical, problem-solving and troubleshooting capabilities.
• Strong communication and stakeholder management skills, with the ability to explain complex technical concepts and trade-offs to both technical and non-technical audiences.

Good to Have

• Experience with Databricks, Unity Catalog, Delta Lake or comparable lakehouse technologies.
• Experience developing data pipelines supporting AI/ML or Retrieval-Augmented Generation (RAG) workloads, such as embedding generation, vector databases/vector stores and retrieval pipelines.
• Knowledge of data governance, metadata management, lineage and access-control practices.
• Experience working in government, public sector, financial services or other regulated environments involving sensitive data.
• Experience with cloud-native deployment platforms, containerisation and modern DevOps/CI/CD practices.
• Relevant cloud, data engineering or Databricks certifications would be advantageous.