Responsibilities

• Partner with Growth, Client Services, Strategy, and Marketing Science teams during pre-sales and discovery phases
• Translate complex client data ecosystems (CRM, CDPs, data warehouses) into clear technical integration plans
• Design approaches to unify CRM data, platform data (GA4, Google Ads, Meta), and offline conversion datasets
• Define data requirements, architecture diagrams, dashboard wireframes, and effort estimates for new engagements
• Own the end-to-end architecture across ingestion (Funnel.io), warehousing (BigQuery), and transformation (Dataform dbt)
• Collaborate with existing data partners to continue building and evolving the current foundation
• Define scalable frameworks for integrating media, CRM, and first-party customer datasets
• Establish industry best practices for data modelling, pipeline orchestration, and warehouse design.
• Ensure the proprietary platform (Salient) remains reliable, scalable, and AI-ready
• Oversee and contribute to the building of robust pipelines using Python for ETL and automation.

Requirements

• Advanced data engineering and architecture design experience in a performance marketing environment
• Strong hands-on experience with BigQuery, Dataform dbt, and Funnel.io (or similar ingestion platforms)
• Proven experience integrating CRM and 1st-party systems like Salesforce, HubSpot, SAP, or custom warehouses
• Experience designing multi-source data models that combine marketing and customer data
• Proven experience working in client-facing or consulting environments
• Ability to translate abstract business problems into concrete technical data solutions
• Skilled in project scoping, including requirements gathering and effort estimation
• Practical experience with AI LLMs, ideally Claude and Gemini
• Familiarity with Reverse ETL tools like Hightouch or Census
• Knowledge of identity resolution and customer data modelling