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Rimes Technologies

Data Reliability Engineer

Reposted 3 Days Ago
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In-Office
Singapore
Mid level
Easy Apply
In-Office
Singapore
Mid level
The Data Reliability Engineer will maintain and optimize data infrastructure, debug ETL processes, and collaborate with teams on data workflows. Requires experience in large-scale data systems and monitoring tools.
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About Rimes

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. 

The Opportunity 

As a Data Reliability Engineer at Rimes Technologies, you will ensure the stability, performance, and resilience of our data platforms that support critical workflows across the global investment ecosystem. This role is ideal for engineers with strong IT infrastructure foundations who can also support data development processes in a modern, data‑driven environment.
You will be responsible for monitoring and optimizing systems, improving observability and automation, troubleshooting resource bottlenecks, and ensuring that data pipelines run smoothly, reliably, and efficiently. This is a high‑impact role where your technical depth directly supports Rimes’ mission of delivering trusted, high‑quality data services to our clients.

What You’ll Do 

  • Own and maintain the core data infrastructure supporting global data delivery. 
  • Maintain and optimize the health of servers supporting data workloads, including monitoring file systems, permissions, logs, and system I/O.
  • 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. 
  • Troubleshoot performance issues across compute, storage, and network layers, escalating as needed and driving permanent fixes.
  • Support the development, maintenance, and reliability of ETL/ELT data pipelines in collaboration with Data Engineering teams.

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. 
  • Strong experience with IT infrastructure, working experience in datacenter or any cloud platform (AWS, Azure, etc.). 
  • Comfortable working with distributed systems / big data projects (SMB clusters, Palantir Foundry, Databricks, etc. are a plus). 
  • Has worked 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.

Visit our Careers page to see our complete listings.

Top Skills

AWS
Azure
Databricks
Datadog
Palantir Foundry
Python
Smb Clusters
SQL

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