Join EY and build a career that's as unique as you are. We are seeking a skilled and experienced Manager – Data Operations to oversee the daily operations of enterprise data pipelines and platforms that support corporate finance transformation. This role offers a blend of hands-on operational management, service oversight, and leadership. You will collaborate with data engineering, platform, governance, and business teams to ensure reliable data delivery for finance processes across P2P, O2C, R2R, and FP&A.

You will be responsible for operational performance, incident coordination, and data quality, driving continuous improvement within your service scope to provide business users with trusted data within agreed service levels.

Manage daily operations for batch and streaming data pipelines, including ingestion, transformation, and delivery. Monitor job execution, data freshness, and dependencies, coordinating necessary reruns and backfills. Maintain comprehensive operational documentation like runbooks and dependency maps. Investigate pipeline failures and data discrepancies using logs and SQL, engaging engineering teams for resolutions. Coordinate production changes and validate operational readiness, release procedures, and post-release checks. Lead incident triage, business impact assessment, and service restoration, ensuring root-cause analysis and corrective actions are completed.

Implement robust incident, problem, and change management practices, ensuring effective shift handovers and on-call coverage. Track and report key operational metrics, using trends to enhance service performance. Automate repetitive tasks and reporting to reduce manual effort and recurring incidents. Execute data quality checks and reconciliations, routing exceptions to data owners and maintaining evidence of resolution and approved controls.

A Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience is required. Candidates should possess 7+ years of experience in data operations, data engineering support, production support, or analytics operations, with a focus on enterprise data services. A minimum of 2 years of team leadership or people management experience is essential, demonstrating a track record of coordinating operational delivery and developing support teams.

Proficiency in supporting data workloads on major cloud platforms (Azure, AWS, or GCP) is crucial, including monitoring, troubleshooting, and access controls. Strong SQL skills, coupled with a solid understanding of ETL/ELT processes, relational databases, data warehouses, and data lake/lakehouse environments, are necessary. Experience with data orchestration tools like Airflow, Azure Data Factory, Spark, dbt, or Kafka is also required, along with working knowledge of Python or shell scripting, APIs, and logging/monitoring tools.

Demonstrated ability to manage production data services against SLAs, prioritize incidents by business impact, and coordinate effective service restoration is key. Familiarity with incident, problem, and change management, release support, runbooks, and root-cause analysis, as well as ITIL, DevOps, or DataOps practices, is beneficial. Exposure to corporate finance processes (P2P, O2C, R2R, FP&A) and finance data flows is preferred, along with experience supporting finance transformation or period-end reporting operations.