Senior Ad Ops Engineer

The Role 

As a Senior Ad Ops Engineer within the Marketing Applied Sciences organization, you will be responsible for architecting and developing advanced, well managed, and reusable data products that support marketing activation, analytics, and insights. You will work extensively with marketing platform data, partner data feeds, and non-standard data formats to build reliable, scalable data pipelines and storage solutions. This role requires deep hands-on experience with marketing ecosystems, digital advertising data structures, and agency or platform-side operations. 

You will also be responsible for implementing automated data quality and validation frameworks, including LLM-powered agents focused solely on data consistency, anomaly detection, and schema integrity. This includes integrating these validation systems directly into production pipelines to ensure accuracy, observability, and compliance across all marketing datasets. 

Additionally, the Senior Ad Ops Engineer will integrate with third-party marketing platforms and APIs, support data discovery across inconsistent partner datasets, and build solutions that provide clean, trustworthy data for activation, measurement, and optimization. 

  What You’ll Do 

 • Architect, build, and optimize data pipelines for marketing and advertising datasets, including nonstandard or semi-structured partner formats 
• Implement data models, storage patterns, and orchestration workflows that support campaign activation, attribution, measurement, and analytics 
• Build and maintain automated data quality and validation systems using LLM-based and rule-based approaches 
• Integrate and normalize data from marketing platforms, digital agencies, and third-party partners, ensuring performance, reliability, and consistency 
• Develop ingestion frameworks for log-level data, event streams, pixel files, and other marketing specific formats 
• Establish and maintain data governance practices including schema tracking, lineage awareness, metadata standards, and privacy compliance 
• Build observability into pipelines with logging, monitoring, and anomaly detection for operational stability 
• Collaborate with cross-functional teams to interpret marketing data requirements and translate them into scalable technical solutions 

Your Skills & Abilities (Required Qualifications) 

• Bachelor’s degree (Master’s preferred) in Computer Science, Data Engineering, Information Systems, or a related technical field 
• 5+ years of experience in data engineering, advertising technology engineering, or marketing data engineering 
• 2+ years of experience working with digital advertising, marketing analytics, digital agencies, or marketing activation platforms 
• Experience with marketing or ad tech ecosystems such as Yahoo, Google, Meta, The Trade Desk, Adobe, Salesforce, or similar 
• Proficiency in Python, SQL, and distributed data frameworks such as PySpark 
• Hands-on expertise working with non-standard marketing data formats, including log-level ad server files, event streams, pixel data, or partner exports 
• Experience with modern data platforms such as Databricks, Snowflake, Kafka, dbt, or Airflow 
• Experience architecting solutions in cloud environments (Azure preferred; AWS/GCP acceptable) 
• Strong understanding of data modeling, warehousing, governance, schema evolution, and data reliability practices 
• Experience building automated or agentic data quality validation systems, including LLM-driven or rules-based frameworks 
• Ability to translate complex marketing data needs into scalable, production-ready engineering solutions 

What Will Give You A Competitive Edge (Preferred Qualifications) ​

• Master’s degree in Computer Science, ML Engineering, Data Engineering, Information Systems, Mathematics, or a related technical field. 

• Experience with real-time or streaming pipelines for marketing activation 
• Experience with Databricks Mosaic AI and LLMOps workflows 
• Familiarity with multi-touch attribution, incrementality, or identity resolution datasets 
• Experience processing large-scale partner or agency data deliveries 

• Experience working with Pseudonymous Identity services