We are building a scalable reporting infrastructure for paid media data and are looking for a senior data engineer to design and implement the core architecture. This is not a dashboard project. This is a data architecture and systems build. The objective is to centralise multi platform ads data into a structured warehouse that can power reliable AI driven querying and operational reporting. Scope of Work Data Ingestion Pull data from multiple ad platforms including: • Google Ads • Meta Ads • Potential future platforms Design resilient ELT pipelines with clear logging and error handling. Data Warehouse Load into a scalable warehouse environment such as: • BigQuery • Snowflake • Redshift Design a clean, extensible schema that handles: • Campaign level • Ad group level • Ad level • Conversion level • Cost and revenue reconciliation The structure must hold up as volume grows. ClickUp API Integration We want to integrate performance data into ClickUp via API to: • Push performance summaries into tasks • Update fields dynamically • Potentially trigger workflow automation Experience with ClickUp API or similar task management APIs is important. AI Query Layer We intend to layer AI driven querying on top of the warehouse. For example: Natural language questions returning reliable structured outputs. We are currently exploring integration with NotebookLM and other AI tooling. You do not need to build the AI model, but the data architecture must support clean semantic querying. What This Is Not • Not a Looker dashboard build • Not a quick Supermetrics export • Not a one off reporting script This is foundational infrastructure. Required Experience • Strong experience with ads data structures • Deep knowledge of ELT pipelines • Cloud data warehouse implementation • Data modelling best practices • API integrations • Schema design for analytics • Experience building systems that are robust, not fragile Bonus: • Experience preparing datasets for AI querying • Familiarity with NotebookLM or LLM powered data workflows • Marketing analytics background