Senior Analytics Engineer, Marketing Sciences

Responsibilities

• Growth Data Pipeline Architecture: Build and maintain scalable systems to ingest data from a wide range of sources, specifically focusing on marketing platforms (Google Ads, Meta), CRM data, and event streams.
• Predictive Model Enablement: Partner with the Growth Analytics team to move predictive models (like pLTV and Churn risk) from research into production-ready data environments.
• Attribution & Demand Modeling: Architect the technical pipelines for Demand Models and LTV:CAC reporting, ensuring company-wide alignment through standardized metrics.
• Experimental Infrastructure: Support the design and execution of A/B tests and causal inference models by ensuring clean, reliable experiment logging and cohort assignment.
• MarTech Integration: Work closely with the MarTech team to optimize our stack and ensure "Source of Truth" consistency across platforms like Iterable, Hubspot, Gong, Segment and more
• Reverse ETL & Activation: Enable "Next Best Action" use cases by syncing data warehouse insights back into product and marketing tools for real-time customer interventions.

Requirements

• Modern Data Stack: Expert proficiency in Snowflake and DBT for creating modular, testable transformations that support complex growth analytics.
• Programming & Scripting: Proficient in Python and SQL, with an "early adopter" mindset toward leveraging modern coding environments and automation to accelerate output.
• Marketing Data Savvy: Proven experience handling semi-structured API data (JSON) from marketing sources and managing the complete lifecycle from ingestion to consumption.
• Segment: Expertise in designing, implementing, and managing Segment event pipelines.
• Strategic Architecture: Ability to lead a technical vision with a holistic view of how data engineering impacts business-critical metrics like LTV, CAC, and ROAS.
• Collaboration: Experience working in an Agile (SCRUM/Kanban) environment, partnering closely with Analysts, Data Scientists, and Marketing Stakeholders.

Preferred

• Experience with Reverse ETL tools (e.g., Census, Hightouch).
• Familiarity with Real-time ETL (Kafka streaming, AWS Kinesis).
• AWS DevOps experience (Terraform, Kubernetes, Docker)

Benefits

• Medical, dental, vision, life & disability insurance
• 401(k) plan with company match
• Flexible Time Off (FTO), wellbeing days, paid holidays, and summer Fridays
• Mental health resources
• Paid parental leave & Backup Care
• Tuition reimbursement
• Employee Resource Groups (ERGs)