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Senior Data Analytics Engineer - Marketing

Posted 10 days agoViewed

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💎 Seniority level: Senior

📍 Location: Australia

🏢 Company: Employment Hero👥 501-1000💰 $166,333,052 Series F over 1 year agoManagement Information SystemsHuman ResourcesSaaSFinanceEmployee Benefits

🪄 Skills: SQLData AnalysisETLMachine LearningGoogle AnalyticsData scienceData visualizationMarketingCRMData modelingData analytics

Requirements:
  • Proficiency in SQL and relational databases.
  • Experience with data pipeline development and ETL processes.
  • Familiarity with visualization tools (e.g., Tableau, Looker Studio).
  • Solid understanding of statistical modeling and machine learning techniques.
  • Expertise in Martech platforms (e.g., CRM, automation, advertising).
  • Strong grasp of Webtech (GA4, GTM, conversion event tracking).
  • Understanding of GTM data layer configuration and conversion tracking.
  • Bachelor’s or Master’s degree in data science, statistics, or a related field.
  • Strong analytical, communication, and problem-solving skills.
  • Knowledge of marketing attribution methods and campaign measurement.
Responsibilities:
  • Build and manage data pipelines to integrate marketing and CRM data into a single source of truth.
  • Resolve integration challenges across multiple marketing platforms, tools, and systems.
  • Simplify complex, cross-channel reporting to support faster, smarter decision-making.
  • Break down MarTech data silos to uncover end-to-end customer and campaign insights.
  • Design and optimise predictive lead scoring models using behavioural, demographic, and firmographic data.
  • Analyse and improve MQL quality by creating data views that highlight fit, intent, and downstream performance.
  • Develop intent models based on user behaviour to power audience segmentation and personalised campaigns.
  • Implement advanced attribution and media mix modelling to fine-tune ad spend and boost ROI.
  • Build smart dashboards and reports that deliver clear, actionable insights to marketing and sales teams.
  • Partner with Marketing to define and track candidate quality metrics across all channels, supporting long-term engagement and re-engagement strategies.
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