Join EY's Global Delivery Services as a Senior DataOps Engineer and drive operational excellence across modern Azure/AWS data platforms. This role offers the chance to own critical data pipelines, contribute to reliability initiatives, and mentor junior engineers. You will be instrumental in enhancing data ingestion, transformation, and monitoring processes, collaborating with diverse teams to troubleshoot complex issues and shape our DataOps strategy. Build an exceptional career in a supportive, inclusive, and globally connected environment.

Ensure the reliability and stability of enterprise data pipelines through proactive monitoring and incident management across cloud platforms. Lead root cause analysis for recurring incidents, implement preventative measures, and establish best practices for system resilience. Mentor junior engineers in incident resolution and process standardization. Collaborate with Data Engineering, DevOps, and Analytics teams to support production deployments and performance optimization. Identify and implement scalable solutions for operational gaps using scripting, automation, and CI/CD practices. Maintain and enhance runbooks, SOPs, and knowledge bases to improve operational processes. Ensure compliance with data governance, logging, observability, and security standards. Participate in on-call rotations and act as an escalation point for complex issues. Manage task execution, optimize processes, and oversee team performance to achieve organizational goals.

A Bachelor's degree in computer science, data analytics, or a related field, or equivalent work experience, is required. Candidates should possess 5-8 years of experience in data operations, data engineering support, or application management. Essential skills include strong experience supporting cloud-based data pipelines and platforms like Databricks and Informatica, expertise in root cause analysis, incident resolution, and monitoring. Proficiency in SQL, Python/PySpark, and CI/CD tools such as Azure DevOps and Git is crucial. Experience architecting and supporting Agentic AI solutions integrated with enterprise data platforms is also a key requirement. Familiarity with global delivery models and excellent stakeholder collaboration skills are necessary. Willingness to participate in 24/7 support rotations is expected.