Overview
Intuit’s Global Business Solutions Group (GBSG) is devoted to creating solutions to meet the needs and improve the chances of success for these entrepreneurs with a portfolio of solutions ranging from mileage tracking to invoicing, payroll to accounting, payments and capital.
We are looking for a senior individual contributor to lead advanced marketing analytics, signal infrastructure, and performance measurement across our platform. This role sits at the intersection of data engineering, applied data science, and marketing performance, with a strong focus on enabling better campaign optimisation, attribution, and full-funnel visibility—especially in a B2B context.
This is a hands-on role for someone who thrives in complex data environments, enjoys building scalable measurement foundations, and can translate data into actionable performance insights for marketing, product, and growth teams.
Responsibilities
Signal & Measurement Infrastructure
- Lead the build and optimization of CAPI and server-side signal capabilities to improve campaign optimization, attribution accuracy, and measurement reliability.
- Partner closely with product, data science, and marketing teams to ensure signal implementation is correct, scalable, and privacy-safe.
Campaign, Creative & Performance Analytics
- Build and maintain performance dashboards covering:
- Creative insights and diagnostics
- Pre-testing frameworks
- Post-campaign performance analysis
- Develop analytics that explain drivers of performance, not just outcomes, enabling faster optimization and learning.
Performance & KPI Dashboarding
- Own ongoing campaign performance dashboards updating key delivery, efficiency, and outcome metrics across channels, platforms and product portfolios.
- Ensure data accuracy, consistency, and decision-readiness for stakeholders across marketing and leadership.
Advanced Analytics Environment
- Operate within a platform-level advanced analytics environment (Meta’s AA; Google’s Big Query / ADH), executing complex queries and large-scale data processing to perform in-depth performance diagnostics or cross-channel measurement.
- Design scalable analytical frameworks that support experimentation, deep dives, and long-term learning.
- Build production-grade analytics workflows rather than ad-hoc analysis.
B2B Full-Funnel & Attribution Reporting
- Build and maintain end-to-end B2B funnel reporting, from leads through MQL, SAL, SQL, and conversion outcomes.
- Establish and maintain data pipelines for B2B attribution reporting, integrating marketing, CRM, and downstream conversion systems.
- Partner with Marketing Ops and Sales Ops to align on definitions, data quality, and reporting logic.
Qualifications
Required Qualifications
- 8+ years of experience in data engineering, data science, or advanced analytics roles, ideally supporting marketing, growth, or revenue organizations.
- Bachelor’s degree in quantitative field such as CS; DS; Statistics; Applied Mathematics or closely related disciplines
- Strong hands-on proficiency in SQL and Python for complex analytics, data processing, and automation.
- Demonstrated experience designing and maintaining data pipelines (ETL/ELT) for analytics, attribution, or performance measurement use cases.
- Experience working in modern data warehouse and lake environments (e.g., BigQuery, Snowflake, Redshift, Databricks, or equivalent).
- Hands-on experience with event-level data, signal ingestion, and data normalization (e.g., CAPI or similar server-side tracking frameworks).
- Proven ability to build scalable, production-grade dashboards and analytical frameworks, not just reporting outputs.
- Strong understanding of marketing and growth data models, including campaign performance, attribution logic, and funnel analysis.
- Comfortable operating as a senior individual contributor with high ownership and autonomy.
Preferred Qualifications
- Master degree or higher in quantitative fields such as CS; DS; Statistics; Applied Mathematics or related disciplines.
- Background in applied data science, including experimentation, statistical analysis, or modeling applied to marketing or growth problems.
- Experience with machine learning techniques (e.g., regression, classification, tree-based models) to support performance prediction, diagnostics, or optimization.
- Hands-on experience with experimentation, incrementality, or causal analysis (A/B testing, geo-lift, holdouts).
- Exposure to AI-assisted analytics workflows, including using LLMs to accelerate analysis, diagnostics, or documentation (with an understanding of limitations).
- Experience working in ad tech, martech, or platform-based data ecosystems.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.