Senior Data Engineer

xtremax pte. ltd.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Xtremax is seeking a Senior Data Engineer in Singapore to design scalable data architectures and build high-performance data pipelines. You will lead cloud-native Data & AI solutions, migrate to multi-cloud environments, and mentor junior engineers while ensuring data governance and security.

The role requires translating business requirements into robust technical specifications and collaborating with stakeholders to deliver scalable, data-driven digital solutions for government and enterprise

Qualifications

• Bachelor's degree in computer science, information technology, computer engineering, or related field.

Responsibilities

• Data Pipeline Infrastructure & Architecture development.
• Design scalable data architectures on cloud platforms with high availability and security.
• Lead Data Lakehouse solutions development.
• Translate requirements into technical specifications for pipelines and data products.
• Build and maintain robust ETL/ELT pipelines.
• Ensure data quality and governance across pipelines and platforms.

Skills

SQL

Python

Apache Spark

Data pipelines

Cloud security

MLOps/LLMOps

DataOps

Stakeholder communication

Education

Bachelor's degree in CS/IT

Tools

Terraform

Kubernetes

Apache Spark

Apache Kafka

Airflow

Python

Job description

Overview

At Xtremax, we help government agencies and enterprises build robust, scalable, and future-ready digital systems. As a Senior Data Engineer, you will play a key role in designing scalable data architectures, translating business requirements into robust technical specifications, and building high-performance data pipelines. This role combines technical leadership, data systems solutioning, and stakeholder collaboration to deliver impactful, data-driven digital solutions. Candidates with public sector experience are preferred, as this role supports IT projects for government agencies.

Responsibility:

• Data Pipeline Infrastructure & Architecture
• Design and implement scalable data architectures on cloud data platforms with high availability, security, and performance
• Lead development of Data Lakehouse solutions
• Collaborate with stakeholders to understand requirements and translate them into technical specifications
• Pipeline Development & Optimisation
• Build and maintain robust ETL/ELT pipelines using modern data engineering tools and frameworks
• Optimise data processing workflows for performance, cost-effectiveness, and reliability
• Implement automated data quality checks and monitoring systems to ensure data integrity
• Data Systems Architecting & Solutioning
• Design and architect comprehensive cloud-native Data & AI solutions aligned with business objectives and technical requirements
• Lead cloud migration strategies and oversee implementation of complex multi-cloud environments
• Drive innovation through integration of Data & AI capabilities into enterprise platform architectures Data & AI platform product architectures
• Conduct technical assessments and recommend modernised approaches using cloud native technologies
• Maintain architectural documentation
• Cloud Platform Operations
• Leverage Cloud Native Services to build and manage data infrastructure
• Implement infrastructure as code practices using Terraform
• Ensure compliance with security standards and data governance policies
• Technical Leadership & Collaboration
• Mentor junior data engineers and provide technical guidance on complex challenges
• Participate in architectural reviews and contribute to data strategy evolution

Requirements:

• Bachelor’s degree in computer science, Information Technology, Computer Engineering, or related field
• Minimum 3 years of relevant experience in data systems architecture, data systems integration, and data pipeline setup at production scale
• Good understanding of cloud computing principles including infrastructure as code, containerisation, microservices architecture, cloud security frameworks, identity and access management, network architecture, and distributed systems
• Proven ability to translate business requirements into technical solutions
• Excellent communication skills for presenting complex concepts to diverse audiences
• Experience with cloud security frameworks, compliance requirements, and risk management
• Experience in data domains (e.g. DataOps, Data Lakehouse) and AI/ML Domains (e.g. MLOps, LLMOps)
• Strong Knowledge and Hands-on experience with SQL, Python and Apache Spark
• Hands-on experience with Apache Kafka, Airflow,or similar technologies

Good to Have (Optional):

• Proficiency in Amazon Web Services (AWS) ecosystem and relevant cloud certifications (e.g., AWS Solutions Architect Professional, AWS Data Engineer Associate).

• Hands-on experience with Data & AI cloud-native services (e.g., Amazon SageMaker, AWS S3, AWS Glue, AWS Lake Formation, AWS Bedrock).

• Familiarity with MLOps, ML model deployment pipelines, serverless computing, edge computing, or IoT architectures.

• Knowledge of metadata management tools, data governance frameworks, or business intelligence / data visualization tools (e.g., Power BI, Tableau).