Explore Manager, Ad Data Operations jobs and discover a pivotal career at the intersection of data strategy, advertising technology, and business leadership. Professionals in this role are the architects of clarity and actionability within the complex ecosystem of digital advertising data. They are responsible for building and maintaining the foundational semantic layer—a unified, business-friendly translation of raw data—that empowers entire organizations to make faster, more confident, data-driven decisions. This position is less about day-to-day campaign analytics and more about constructing the robust, scalable data infrastructure that makes all analytics possible, ensuring that key performance indicators (KPIs) are consistent, reliable, and accessible to both technical and non-technical stakeholders. Typically, a Manager of Ad Data Operations bridges the gap between business needs and technical execution. Common responsibilities include translating complex business logic and advertising metrics into scalable data models using tools like SQL and modern transformation frameworks. They lead the design of dimensional models that standardize metric definitions across marketing, product, and executive teams, preventing conflicting data interpretations. A significant part of the role involves collaboration; they act as a crucial liaison between product managers, data engineers, product analysts, and business leaders to gather requirements and ensure the semantic layer delivers clear, actionable insights. Furthermore, they own the development standards for this layer, implementing best practices for version control, automated testing, performance optimization, and code reviews to ensure data quality and integrity at scale. The typical skill set for these jobs blends deep technical expertise with strong business acumen and communication skills. Candidates generally require proficiency in cloud data platforms (e.g., Snowflake, BigQuery, Redshift), advanced SQL, and data modeling tools like dbt. A solid understanding of data warehousing principles, ELT/ETL architecture, and dimensional modeling (e.g., Star Schema) is essential. Equally important are the soft skills: the ability to manage stakeholders, explain intricate data concepts to non-technical audiences, and drive organization-wide adoption of metric governance frameworks. A background in computer science, data engineering, or a related field, coupled with several years of experience in data modeling or technical analysis within an advertising or martech context, is commonly expected. For those who thrive on creating order from complexity and enabling smarter business decisions, Manager, Ad Data Operations jobs offer a challenging and high-impact career path.
