Build Marketing Data Integrations for Creation and Ongoing Use of Reporting Dashboard

We are seeking an experienced marketing data engineer / automation developer to build an automated cross-channel marketing analytics and reporting system. Project Objective Our goal is to consolidate data from multiple marketing and analytics platforms into a centralized data repository, automate recurring reporting, and create a dashboard that allows our team to evaluate marketing performance across channels. We are also interested in incorporating AI-driven workflows that can analyze the consolidated data and surface useful observations or recommendations. Phase 1 Data Sources The initial project will integrate six sources: -Google Analytics 4 -Google Ads -Microsoft Advertising -LinkedIn Ads -LinkedIn Page Analytics -SEMrush Note: A potential future phase may add additional sources including YouTube, Wistia and BusinessWire. Desired Functionality The completed system should: -Automatically retrieve data from the supported platforms through their APIs. -Normalize and consolidate marketing data from the different sources. -Store the resulting data in a centralized data warehouse or repository. -Automate recurring data collection and reporting workflows. -Provide a dashboard for viewing marketing performance across channels. -Allow us to compare paid-media performance across Google, Microsoft and LinkedIn. -Incorporate website and owned-social performance from GA4 and LinkedIn. -Incorporate competitor insights from SEMrush. -Include data-quality monitoring to identify missing or incomplete fields. -Support automated notifications or reports through Slack or Microsoft Teams. -Explore the use of AI/LLM workflows to analyze results and provide actionable marketing recommendations. Technology Our current proposed architecture includes: -n8n or similar for workflow/API orchestration -SQL -A centralized data warehouse such as Google BigQuery or Snowflake -Sigma for dashboarding and visualization -Claude/Anthropic and MCP for AI-assisted analysis and recommendations -JavaScript as needed for custom integrations We are open to recommendations regarding the architecture if you have experience building similar systems and believe an alternative would be more reliable, maintainable or cost-effective. Required Experience We are particularly interested in candidates with experience in: -n8n or comparable workflow automation platforms -REST APIs and API integrations -SQL and data modeling -ETL/ELT and automated data pipelines -BigQuery, Snowflake or comparable cloud data warehouses -Marketing analytics and advertising data -Google Analytics 4 and advertising-platform APIs -JavaScript for custom API/workflow development -Experience with LinkedIn APIs, Microsoft Advertising, SEMrush, Sigma, Claude/Anthropic, MCP or other LLM-based agentic workflows is strongly preferred. Ownership & Maintainability All technology accounts, workflows, code, API connections and data repositories created for this project must be owned by our company. An important objective is maintainability. The completed system should be documented sufficiently so that its ongoing management can be transferred to another internal or external technical resource in the future. When Responding Please include: -Examples of similar marketing data integration or automated reporting systems you have built. -The APIs and marketing platforms you have previously integrated. -Your experience with n8n, SQL and cloud data warehouses. -Your experience incorporating AI/LLMs into automated data-analysis workflows. -Your recommended architecture for this project and any changes you would suggest to the technology stack described above. -Your estimated hours, timeline and cost for completing Phase 1. -Any ongoing software, API or infrastructure costs we should anticipate. -Your approach to documentation and handoff at the end of the project. We are specifically looking for someone who has built production-quality data integrations and automated reporting systems, rather than someone whose experience is limited primarily to creating dashboards.