Manager – Product Operations

Role Overview

The Manager – Data Operations will manage the day-to-day operation of enterprise data pipelines and platforms supporting corporate finance transformation. This role combines hands-on operational oversight, service management, and team leadership to ensure timely, accurate, and reliable data delivery.

What You Will Do

The ideal candidate will work closely with data engineering, platform, governance, and business teams to support finance processes across P2P, O2C, R2R, and FP&A. You will be accountable for operational performance, incident coordination, data quality monitoring, and continuous improvement within the assigned service scope.

Why It Might Be a Fit

The ideal candidate will have 7+ years of experience in data operations, data engineering support, production support, or analytics operations, including responsibility for enterprise data services. 2+ years of team leadership or people-management experience is also required.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience
• 7+ years of experience in data operations, data engineering support, production support, or analytics operations, including responsibility for enterprise data services
• 2+ years of team leadership or people-management experience, with a track record of coordinating operational delivery and developing support teams
• Hands-on experience supporting data workloads on at least one major cloud platform (Azure, AWS, or GCP)
• Strong SQL skills and understanding of ETL/ELT processes, relational databases, data warehouses, and data lake or lakehouse environments
• Experience with data orchestration and processing tools relevant to the environment (e.g., Airflow, Azure Data Factory, Spark, dbt, or Kafka)
• Working knowledge of Python or shell scripting, APIs, file-based integrations, logging, and monitoring tools to automate checks and investigate data flow issues
• Understanding of data quality, reconciliation, lineage, role-based access, sensitive-data handling, and enterprise governance requirements