Marketing Analytics Lead

About the Role

This role, based in Australia, involves leading marketing analytics to drive data-based marketing decisions within a rapidly expanding technology firm. The Marketing Analytics Lead will translate intricate marketing datasets into insightful, actionable intelligence to guide marketing investments, improve campaign effectiveness, and boost revenue growth.

Working in partnership with marketing, analytics, engineering, and commercial departments, this position entails creating scalable data models, attribution methodologies, and business intelligence tools. Additionally, the role empowers stakeholders through dependable self-service analytics while enhancing comprehension of the entire marketing funnel. Ideal for analytical leaders passionate about resolving complex challenges and crafting impactful data products at scale.

Key Responsibilities

• Derive actionable insights from complex, multi-source marketing data to inform channel investment, campaign optimization, and pipeline development.
• Collaborate across demand generation, partner marketing, field marketing, product marketing, and brand teams to execute effective analytics projects.
• Create and maintain marketing attribution frameworks including first-touch, multi-touch, and incrementality measurement models.
• Develop dashboards, reporting systems, and self-service analytics platforms for stakeholders to track funnel metrics, channel ROI, and campaign results.
• Coordinate with data engineering teams to produce scalable marketing data models and foundational analytics assets utilizing modern data infrastructure.
• Perform comprehensive analyses to detect trends, diagnose marketing issues, and propose strategic enhancements.
• Link marketing spend to commercial outcomes such as pipeline expansion, annual recurring revenue (ARR), customer acquisition cost, and payback periods.
• Continuously enhance marketing measurement approaches, reporting precision, and data governance standards.

Candidate Requirements

• At least four years of experience providing marketing analytics solutions in a fast-growing SaaS environment.
• Strong knowledge of digital marketing channels, attribution approaches, marketing mix modeling, and performance analytics.
• Proven ability to convert ambiguous business needs into scalable data models, metrics, and reporting frameworks.
• Proficiency with modern analytics tools such as cloud data warehouses, dbt, ETL/ELT pipelines, and BI platforms like Looker or ThoughtSpot.
• Experience with marketing platforms including HubSpot, Salesforce, Google Ads, LinkedIn Ads, Meta, or similar technologies.
• Advanced SQL and data modeling skills to develop reliable business intelligence assets.
• Excellent analytical reasoning and problem-solving capabilities, adept at conveying complex insights to both technical and non-technical stakeholders.
• Strong cross-functional collaboration and stakeholder management expertise.
• Consulting background, familiarity with AI or data science initiatives, and financial analytics experience are valuable additions.

Benefits

• Fully remote working arrangement with optional usage of office locations.
• Monthly lifestyle allowance promoting physical, mental, and financial wellness.
• Home office setup support provided upon onboarding.
• Annual Learning & Development budget of USD 1,500.
• Paid annual leave plus two extra wellness days.
• 18 weeks paid parental leave for all parents.
• Paid personal, sick, and caregiver leave.
• Provision of a high-performance laptop and necessary equipment.
• Company-sponsored access to generative AI tools.
• Opportunities to advance within a globally recognized, high-performing technology company working alongside talented international teams.

Additional Information

This opportunity is managed by a partner organization that receives and processes applications directly. The hiring decisions and subsequent steps like interviews and assessments are handled internally by the partner company.

Applications are reviewed promptly using AI-assisted processes aimed at objective and fair evaluation based on core qualifications. However, final hiring choices are made by humans.

Data privacy is respected in accordance with applicable laws, with candidates able to exercise their data rights. AI technologies might aid in recruitment steps, but do not replace human judgment.