Role Overview
We are looking for a Data Platform Reliability Engineer to join our Global Data team. This role focuses on enabling reliable, scalable, and self-service data platforms built on modern cloud technologies such as Google BigQuery Lakehouse architectures, and distributed data pipelines.
You will play a key role in supporting production data platforms, improving platform observability, and empowering users through automation, AI-driven capabilities, and self-service solutions.
Key Responsibilities
Leverage AI/GenAI tools to improve data discovery, metadata generation, and operational efficiency
Build and enhance data observability frameworks (data freshness, data quality, pipeline health)
Monitor and troubleshoot data pipelines, ingestion, and transformation workflows
Enable self-service data access for business users through well-defined datasets, documentation, and tools
Automate repetitive support tasks using scripting and platform-native capabilities
Collaborate with engineering, analytics, and business teams to resolve data issues and improve platform usability
Provide support for enterprise data platforms, ensuring high availability and reliability
Support data governance initiatives, including metadata, lineage, and cataloging
Participate in incident management, root cause analysis, and continuous improvement efforts
Required Skills & Experience
3–4 years of experience in data engineering / data platform support
Strong hands-on experience with Google BigQuery, GCS, Composer
Experience working with data lakehouse architectures (e.g., BigQuery, DBT)
Good understanding of data ingestion and transformation tools (e.g., Airflow, Composer, Informatica CDC, dbt, or similar)
Proficiency in SQL and Python
Experience with cloud platforms (GCP preferred; AWS/Azure is a plus)
Familiarity with data pipeline monitoring and troubleshooting
Basic understanding of data governance and metadata management tools (e.g., Collibra or similar)
Preferred Skills
Experience with data observability tools/frameworks
Exposure to AI/ML or GenAI tools in data workflows
Knowledge of Collibra or similar Data Governance tools
Knowledge of Looker / Tableau / Power BI or similar BI tools
Experience with CI/CD and DevOps practices in data environments
Understanding of cost optimization (FinOps) in cloud data platforms
What You Will Bring
Strong problem-solving and analytical mindset
Passion for improving platform reliability and user experience
Excellent communication and collaboration skills
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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Who we are:
At Pearson, our purpose is simple: to help people realize the life they imagine through learning. We believe that every learning opportunity is a chance for a personal breakthrough. We are the world's lifelong learning company. For us, learning isn't just what we do. It's who we are. To learn more: We are Pearson.
Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are based on qualifications, merit and business need. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status or any other group protected by law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
If you are an individual with a disability and are unable or limited in your ability to use or access our career site as a result of your disability, you may request reasonable accommodations by emailing [email protected].
Job: Data Engineering
Job Family: TECHNOLOGY
Organization: OCTO
Schedule: FULL_TIME
Workplace Type: Hybrid
Req ID: 24176
