Data Reliability Engineer

Company Description Rockland Tech Hub is a technology solutions provider that helps startups, growing businesses, and enterprises modernize systems, streamline operations, and build secure, scalable digital platforms. The company delivers services including reliable IT support, intelligent automation, custom software development, web and mobile applications, e-commerce solutions, software testing, branding support, and IT staffing. Rockland Tech Hub’s multidisciplinary team combines deep technical expertise with practical business insight to create solutions that improve efficiency, strengthen performance, and support sustainable growth. Clients rely on the organization for responsive websites, custom business applications, workflow automation, quality assurance, and access to skilled IT professionals, all tailored to their specific goals.
Role Description The Data Reliability Engineer is a full-time remote role responsible for ensuring the robustness, availability, and integrity of data systems and pipelines. This role involves designing and implementing reliability practices, monitoring data flows, identifying bottlenecks, and proactively resolving issues to minimize downtime and data loss. The engineer will perform failure analysis on data infrastructure, collaborate with data engineers and developers to improve system designs, and apply reliability-centered maintenance principles to databases, ETL processes, and analytics platforms. Day-to-day tasks include troubleshooting incidents, optimizing performance, maintaining documentation, enhancing observability through logs and metrics, and contributing to automation and tooling that support reliable, scalable data operations.
Qualifications
Demonstrated experience in Reliability Engineering, including designing and implementing reliability strategies for data systems.
Strong Analytical Skills and experience with Failure Analysis to diagnose root causes of data incidents and performance issues.
Knowledge of Reliability Centered Maintenance concepts and their application to data infrastructure and critical services.
Proficiency in Troubleshooting complex data pipelines, databases, and cloud-based platforms.
Experience with data engineering tools and technologies (e.g., SQL/NoSQL databases, ETL/ELT frameworks, data warehouses, streaming platforms).
Familiarity with monitoring, logging, and alerting tools (e.g., Prometheus, Grafana, Datadog, ELK, or similar) and building dashboards for reliability metrics.
Comfort working in cloud environments (such as AWS, Azure, or GCP) and using infrastructure-as-code or automation tools.
Effective communication skills and ability to collaborate with cross-functional teams in a remote environment.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
Experience in IT services, software development, or technology consulting environments is beneficial.

Work arrangement
Yes