Shape your career with EY and become the best version of yourself, leveraging global scale and an inclusive culture. We are seeking a skilled Manager – Data Operations to oversee enterprise data pipelines and platforms vital for corporate finance transformation. This role merges hands-on operational management with team leadership, ensuring reliable data delivery. You'll collaborate with data engineering, platform, governance, and business teams to support P2P, O2C, R2R, and FP&A finance processes. Accountable for operational performance, incident coordination, and data quality, you will empower business users with trusted data within defined service levels.

Manage daily operations for batch and streaming data pipelines, including ingestion, transformation, and delivery. Monitor job execution, data freshness, and processing volumes, coordinating recovery efforts. Maintain operational documentation like runbooks and standard operating procedures. Troubleshoot pipeline failures and data discrepancies, engaging engineering teams as needed. Coordinate production changes and releases, ensuring operational readiness and post-release validation. Lead incident triage, impact assessment, and service restoration, facilitating root-cause analysis. Implement incident, problem, and change management practices. Track and report on key operational metrics, identifying trends for service improvement. Automate repetitive tasks and work towards reducing manual effort and recurring incidents. Execute data quality checks and reconciliations, managing exceptions with data owners.

A Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience is required. You should have 7+ years of experience in data operations, production support, or analytics operations, with at least 2 years in team leadership or people management. Hands-on experience with major cloud platforms (Azure, AWS, GCP) is essential, along with strong SQL skills and a solid understanding of ETL/ELT processes, databases, and data warehousing. Familiarity with data orchestration tools like Airflow or Azure Data Factory, and scripting in Python or shell is necessary. Experience with incident, problem, and change management, along with ITIL or DataOps practices, is highly beneficial. Exposure to corporate finance processes is a plus.