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Data Reliability Engineer

Rimes Technologies

Singapore

On-site

SGD 70,000 - 90,000

Full time

Yesterday
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Job summary

A leading data management firm in Singapore is looking for a hands-on Data Reliability Engineer. The successful candidate will maintain and optimize data infrastructure for analytics, utilizing Python and SQL along with observability tools to enhance performance. Responsibilities include profiling ETL systems and collaborating with diverse teams on big data projects. A degree in Computer Science or Engineering is required. Join a dynamic team improving opportunities for all.

Qualifications

  • Hands-on engineer with strong proficiency in Python and SQL.
  • Experienced in profiling and optimizing ETL systems and large-scale data pipelines.
  • Familiar with IT infrastructure or cloud platform experience.

Responsibilities

  • Profile, debug, and optimize large-scale ETL and data processing pipelines.
  • Write and maintain Python and SQL code for data workflows.
  • Use observability tools to monitor and resolve system bottlenecks.

Skills

Python
SQL
Data processing pipelines
ETL systems
Cloud platforms (AWS, Azure)
Monitoring tools (Datadog)
Problem-solving skills

Education

Degree in Computer Science or Engineering

Tools

Datadog
Palantir Foundry
Databricks
Job description

Rimes provides enterprise data management solutions to the global investment community. Driven by our passion for solving the most complex data problems, we provide our clients with investment intelligence that powers more than US$75 trillion in assets under management annually. The world’s leading institutional investors, asset managers and service providers rely on Rimes to help them make better investment decisions using accurate information and industry‑leading technology.

We are currently in an exciting phase of transformation, re‑platforming and enhancing our working practices.

Opportunity

We are looking for a hands‑on Data Reliability Engineer to join our team. This role is focused on maintaining and optimizing the data infrastructure that powers Rimes’ global platforms. We seek strong technical engineers first—those with experience profiling, tuning, and scaling large‑scale data and ETL systems. Over time, there is potential to grow into a team lead role.

What You’ll Do
  • Profile, debug, and optimize large‑scale ETL and data processing pipelines for performance and reliability.
  • Write and maintain Python and SQL code to support data workflows, modules, and archiving processes.
  • Use Datadog and other observability tools to proactively monitor, detect, and resolve system bottlenecks.
  • Collaborate with Data Developers, SRE, and Infrastructure teams to ensure system scalability and disaster recovery readiness.
  • Contribute to projects involving big data platforms, SMB clusters, and Palantir Foundry.
  • Continuously improve automation, processes, and system resilience.
Who You Are
  • Hands‑on engineer with strong proficiency in Python and SQL.
  • Experienced in profiling and optimizing ETL systems and large‑scale data pipelines.
  • Familiar with IT infrastructure; working experience in a data centre or any cloud platform (AWS, Azure, etc.) will be a plus.
  • Comfortable working with distributed systems / big data projects (SMB clusters, Palantir Foundry, Databricks, etc. are a plus).
  • Familiar with monitoring and observability tools (Datadog or similar).
  • Strong problem‑solver with the ability to dive deep into complex technical issues.
  • Financial services or exposure to data‑intensive domains is preferred.
  • Degree in Computer Science, Engineering, or equivalent practical experience.

Only selected candidates will be contacted for interviews. We appreciate your understanding. Thank you for considering a career with us.

Rimes is committed to promote the values of diversity and inclusion throughout the business. Whether it’s through recruitment, retention, career progression or training and development, we are committed to improving opportunities for people regardless of their background or circumstances.

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