Data Engineer (3 Year Contract)

RHINO PARTNERS PTE. LTD.; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

RHINO PARTNERS PTE. LTD. seeks a Data Engineer to design, build and optimise cloud-native data platforms for enterprise analytics and AI. You will shape data lakehouse architectures, drive DataOps practices, and mentor junior engineers across cloud migrations and AI integrations.

Responsibilities include designing scalable pipelines, implementing IaC with Terraform, and delivering secure, reliable data solutions while collaborating with analytics and business teams.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Computer Engineering, or a related discipline.
• Minimum 3 years of experience in data engineering, data architecture, or enterprise data platform development.
• Strong hands-on experience building production-scale data pipelines and cloud-native data platforms.
• Strong proficiency in Python, SQL, Apache Spark.
• Experience with modern data engineering tools such as Apache Kafka, Apache Airflow (or similar workflow orchestration tools).
• Good understanding of Cloud computing principles, Terraform, containerisation, microservices, distributed systems, cloud networking, IAM, cloud security.
• Experience with DataOps, Data Lakehouse, or modern data platform architectures.
• Familiarity with AI/ML platform operations including MLOps or LLMOps.
• Strong analytical, problem-solving, and communication skills.
• Ability to translate business requirements into scalable technical solutions.

Responsibilities

• Design scalable, secure, and highly available cloud-based data platforms.
• Architect and develop modern Data Lakehouse solutions.
• Gather requirements and translate into scalable technical solutions.
• Produce and maintain architecture documentation and standards.
• Develop and maintain robust ETL/ELT pipelines; optimise performance and cost.
• Implement automated data quality validation, monitoring, and alerting.
• Lead cloud migration initiatives and support multi-cloud deployments.
• Mentor junior data engineers and contribute to data strategy.

Skills

Data engineering

Data architecture

Cloud-native platforms

Python

SQL

Apache Spark

DataOps

AI/ML platform ops

Problem solving

Communication

Education

Bachelor's degree in Computer Science, Information Technology, Computer Engineering, or related discipline

Tools

Apache Kafka

Apache Airflow

Terraform

Job description

About the job

We are looking for a Data Engineer to design, build, and optimise modern cloud-native data platforms that power enterprise-scale analytics and AI initiatives. You will play a key role in developing scalable data architectures, implementing high-performance data pipelines, and enabling data-driven decision-making across the organisation.

Working within a collaborative engineering team, you will contribute to Data Lakehouse architectures, cloud migration initiatives, DataOps practices, and the integration of AI capabilities into enterprise data platforms while mentoring junior engineers and driving engineering best practices.

Key Responsibilities

Cloud Data Platform & Architecture

• Design and implement scalable, secure, and highly available cloud-based data platforms.
• Architect and develop modern Data Lakehouse solutions.
• Work closely with stakeholders to gather business requirements and translate them into scalable technical solutions.
• Produce and maintain architecture documentation and technical standards.

Data Engineering & Pipeline Development

• Develop and maintain robust ETL/ELT pipelines using modern data engineering frameworks.
• Build reliable, production-grade data ingestion and transformation workflows.
• Optimise pipeline performance, scalability, reliability, and cloud cost efficiency.
• Implement automated data quality validation, monitoring, and alerting.

Cloud Solution Architecture

• Design cloud-native Data & AI solutions aligned with business and technical objectives.
• Lead cloud migration initiatives and support complex multi-cloud deployments.
• Integrate AI capabilities into enterprise data platforms.
• Evaluate emerging technologies and recommend modern cloud-native approaches.

Cloud Infrastructure & Operations

• Build and manage cloud infrastructure using native cloud services.
• Implement Infrastructure as Code (IaC) using Terraform.
• Ensure platforms comply with security standards, governance policies, and operational best practices.
• Support platform reliability, monitoring, and continuous improvement.

Technical Leadership

• Mentor and guide junior data engineers on technical implementation and best practices.
• Participate in architecture reviews and contribute to the evolution of the organisation's data strategy.
• Collaborate with cross-functional engineering, analytics, and business teams.

Requirements

Essential Skills & Experience

• Bachelor's degree in Computer Science, Information Technology, Computer Engineering, or a related discipline.
• Minimum 3 years of experience in data engineering, data architecture, or enterprise data platform development.
• Strong hands-on experience building production-scale data pipelines and cloud-native data platforms.
• Strong proficiency in:
  • Python
  • SQL
  • Apache Spark
• Experience with modern data engineering tools such as:
  • Apache Kafka
  • Apache Airflow (or similar workflow orchestration tools)
• Good understanding of:
  • Cloud computing principles
  • Infrastructure as Code (Terraform)
  • Containerisation
  • Microservices architecture
  • Distributed systems
  • Cloud networking
  • Identity & Access Management (IAM)
  • Cloud security best practices
• Experience with DataOps, Data Lakehouse, or modern data platform architectures.
• Familiarity with AI/ML platform operations including MLOps or LLMOps.
• Strong analytical, problem-solving, and communication skills.
• Ability to translate business requirements into scalable technical solutions.

Nice to Have

• Experience with Amazon Web Services (AWS) .
• Experience with AWS services such as:
  • S3
  • Glue
  • Lake Formation
  • SageMaker
  • Bedrock
  • Amazon Quick Suite
• AWS certifications such as:
  • AWS Certified Solutions Architect - Professional
  • AWS Certified Data Engineer - Associate
• Experience with machine learning deployment pipelines and MLOps.
• Knowledge of metadata management and data governance frameworks.
• Familiarity with serverless computing, edge computing, or IoT architectures.
• Experience with business intelligence or data visualisation platforms.

Why Join Us?

• Work on enterprise-scale cloud and AI data platforms.
• Design and build modern Data Lakehouse architectures.
• Be part of large-scale cloud transformation initiatives.
• Collaborate with experienced engineers on cutting-edge data and AI technologies.
• Opportunity to mentor engineers while shaping the future of enterprise data platforms.