Data Platform Reliability Engineer

Advanced Specialist, Technology Data Analyst

Role Overview 

We are looking for a Data Platform Reliability Engineer to ensure the reliability, scalability, and performance of our enterprise data platform. This role blends Site Reliability Engineering (SRE) and DevOps practices to support modern cloud-based data ecosystems built on Google BigQuery, lakehouse architectures, and distributed data pipelines. 

You will play a key role in building highly resilient, governable, observable, and cost-efficient data platforms, while enabling engineering teams to operate at scale with automation and best practices. 

Key Responsibilities 

• Automate infrastructure provisioning and operations using Infrastructure as Code (IaC)  
• Implement and manage CI/CD pipelines for data and platform deployments  
• Implement and manage Data Governance tools such as Collibra 
• Improve system resilience through capacity planning, performance tuning, and fault tolerance design  
• Optimize cloud usage and costs through FinOps best practices  
• Collaborate with engineering and analytics teams to improve platform reliability and developer experience  
• Drive security, compliance, and access control best practices 
• Own platform reliability and availability for enterprise data systems (SLAs, SLOs, error budgets)  
• Monitor and manage data cloud infrastructure, ingestion frameworks, and transformation workflows  
• Lead incident management, root cause analysis (RCA), and postmortems  

 

Required Skills & Experience 

• 3–5 years of experience in SRE, DevOps, or platform engineering roles 
• Strong experience with cloud platforms (GCP preferred; AWS/Azure is a plus) 
• Experience with CI/CD tools (GitHub Actions, Jenkins, etc.) 
• Proficiency in Python, Bash, and SQL 
• Experience with Infrastructure as Code tools (Terraform preferred) 
• Strong understanding of monitoring and observability tools (logs, metrics, tracing) 
• Experience managing production incidents and on-call rotations 
• Exposure to Kubernetes / containerization 
• Understanding of data governance and security practices 
• Exposure to AI/ML or GenAI tools for automation and operational efficiency 

 

Preferred Skills 

• Experience with data observability tools/frameworks  
• Knowledge of Collibra or similar Data Governance tools  
• Knowledge of Looker / Tableau / Power BI or similar BI tools  
• Understanding of cost optimization (FinOps) in cloud data platforms  

 

What You Will Bring 

• Strong ownership mindset and bias for automation 
• Ability to troubleshoot complex distributed systems under pressure 
• Passion for improving system reliability and performance at scale 
• Excellent collaboration and communication skills 
• Willingness to participate in a 24/7 support/on-call rotation

 

Why Join Us 

• Build and scale next-gen cloud data platforms powering enterprise-wide analytics 
• Join Pearson, a global leader transforming lives through learning and innovation 
• Work hands-on with GenAI, AI-powered data engineering, and intelligent automation 
• Shape the future of self-service data, data products, and observability at scale 
• Collaborate with high-performing global teams solving real-world, high-impact problems 

• Accelerate your career in a fast-evolving, innovation-driven data ecosystem

   

   

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Experience Level

Senior Level