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
#LI-P1
Skills Required
- 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
- Willingness to participate in a 24/7 support/on-call rotation
- 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 We Do
We are the world’s learning company with more than 22,500 employees operating in 70 countries. We provide content, assessment and digital services to learners, educational institutions, employers, governments and other partners globally. We are committed to helping equip learners with the skills they need to enhance their employability prospects and to succeed in the changing world of work. We believe that wherever learning flourishes so do people.
