Senior Data Engineer (1 Year Contract)

RHINO PARTNERS PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Rhino Partners is seeking an experienced Senior Data Engineer to support a large-scale digital transformation for Singapore's public sector. You will design, build, and maintain scalable data platforms and pipelines to transform procurement processes and improve service for public officers and suppliers.

Responsibilities include implementing DataOps best practices, CI/CD, and data governance, while collaborating with cross-functional teams to deliver reliable, secure data solutions that scale

Qualifications

• Bachelor's degree in Computer Science, Data Science, IT, Statistics, Applied Mathematics, or related field.
• Minimum 5 years hands-on data engineering experience in large-scale environments.
• Proficiency in Python, Scala or Java.
• Solid ETL/ELT and data integration skills.
• Knowledge of OLTP/OLAP/dimensional modelling.
• Experience with cloud data platforms and big data tech.
• Familiarity with CI/CD and DataOps practices.
• Understanding of data governance, security, privacy, and quality.

Responsibilities

• Design, develop, and maintain scalable data platforms and architectures.
• Build and optimise ETL/ELT pipelines for ingestion, transformation, and processing.
• Develop data models (OLTP/OLAP) to support complex business needs.
• Implement data integrations via APIs, streaming, CDC, and message queues.
• Work with cloud data lakes and big data technologies to support enterprise-scale processing.
• Improve pipeline reliability, data quality, and operational efficiency.
• Translate requirements into scalable engineering solutions and guide junior engineers.

Skills

Python/Scala/Java

ETL/ELT pipelines

Data modelling

Cloud platforms

Big data tech

Data governance

CI/CD / DataOps

Stakeholder mgmt

Education

Bachelor's degree

Tools

AWS

Azure Synapse

Snowflake

Databricks

Redshift

Job description

Rhino Partners is seeking an experienced Senior Data Engineer to support a large-scale digital transformation initiative within Singapore's public sector.

You will be involved in the development and enhancement of a next-generation government procurement platform designed to transform procurement processes and improve the experience for public officers and external suppliers across the Whole of Government (WOG).

In this role, you will design, develop, and maintain scalable data platforms, pipelines, and integration solutions that support complex enterprise data requirements. You will work closely with cross-functional teams to deliver reliable, secure, and high-performing data solutions while driving DataOps best practices and continuous improvements.

Key Responsibilities

Data Engineering & Platform Development

• Design, develop, and maintain scalable, reliable, and maintainable data platforms and architectures.

• Build and optimise ETL/ELT pipelines to support data ingestion, transformation, processing, and integration.

• Develop and implement data models, including OLTP, OLAP, and dimensional modelling, to support complex business requirements.

• Implement data integration solutions using APIs, data streaming, Change Data Capture (CDC), and message queues.

• Work with cloud-based data platforms, data lakes, and big data technologies to support enterprise-scale data processing.

• Optimise data pipelines and systems for performance, scalability, and reliability.

DataOps & Engineering Best Practices

• Implement and enhance DataOps practices, including CI/CD pipelines, automated deployments, workflow monitoring, and data observability.

• Establish automated processes to improve data quality, pipeline reliability, and operational efficiency.

• Troubleshoot complex data engineering issues, identify root causes, and implement sustainable solutions.

• Proactively refactor existing solutions and address technical debt to improve system maintainability.

• Ensure compliance with data governance, security, privacy, and regulatory requirements.

Solution Delivery & Collaboration

• Translate business and technical requirements into scalable data engineering solutions.

• Take ownership of data engineering initiatives from solution design through implementation, testing, and deployment.

• Collaborate with application developers, architects, infrastructure teams, and business stakeholders to deliver integrated solutions.

• Identify technical risks, dependencies, and opportunities for improvement.

• Provide technical guidance and mentorship to junior engineers, promoting engineering best practices and knowledge sharing.
  

Requirements

• Bachelor's degree in Computer Science, Data Science, Information Technology, Statistics, Applied Mathematics, or a related discipline.

• Minimum 5 years of hands‑on experience in data engineering, preferably within large-scale enterprise environments.

• Strong proficiency in at least one programming language, such as Python, Scala, or Java.

• Solid experience in designing and developing ETL/ELT pipelines and complex data integration solutions.

• Strong understanding of data modelling concepts, including OLTP, OLAP, and dimensional modelling.

• Experience with cloud data platforms and technologies such as AWS, Azure Synapse, Microsoft Fabric, Snowflake, Databricks, Redshift, or Data Lakes.

• Familiarity with big data processing and streaming technologies such as Apache Spark, Kafka, Hadoop, or Flink.

• Experience with data integration approaches, including APIs, streaming, CDC, and message queues.

• Hands‑on experience with CI/CD pipelines, automated deployments, and DataOps practices.

• Understanding of data governance, security, privacy, and data quality management.

• Strong analytical, troubleshooting, and problem‑solving skills.

• Good communication and stakeholder management skills, with the ability to work independently and collaborate across teams.
  

Good to Have

• Experience with SHIP-HATS or similar government cloud and DevOps environments.

• Exposure to machine learning, Large Language Models (LLMs), prompt engineering, or AI application development.

• Familiarity with MLOps practices and cloud‑based machine learning deployment.

• Understanding of responsible AI principles, including fairness, robustness, and safety.

• Prior experience delivering data platforms or digital transformation initiatives within the public sector.
  

Why Join Us?

• Contribute to a major government digital transformation initiative with meaningful nationwide impact.

• Work with modern cloud data platforms, big data technologies, and enterprise integration solutions.

• Gain exposure to complex, large-scale data engineering challenges.

• Collaborate with experienced technology professionals in an environment that encourages ownership, innovation, and continuous learning.