AI & Analytics Engineer
Role Overview
Build data foundations for client marketing decisions by transforming raw GA4, media and CRM data into trusted modeled datasets in BigQuery.
The team covers measurement strategy, tagging and implementation, data engineering, reporting and applied AI.
The role is a full-time, permanent, mid-level hire in Sydney or Melbourne, with a hybrid work arrangement.
The role works with enterprise clients and a mix of short projects and longer-running data products.
Key Skills for This Role
Full Job Posting
About Monks
Monks is a digital-first marketing, technology and creative consultancy operating across creativity, media, data and culture.
Its APAC team has 700 employees across 14 offices in 11 countries.
The company develops AI-native workflows, custom agent solutions, AI-driven campaigns and next-generation AI search capabilities.
Role overview
Build data foundations for client marketing decisions by transforming raw GA4, media and CRM data into trusted modeled datasets in BigQuery.
The team covers measurement strategy, tagging and implementation, data engineering, reporting and applied AI.
The role is a full-time, permanent, mid-level hire in Sydney or Melbourne, with a hybrid work arrangement.
The role works with enterprise clients and a mix of short projects and longer-running data products.
Pipelines and measurement
- Build and maintain BigQuery pipelines for GA4 exports, ad platforms including Google Ads, DV360, Meta and CM360, and client CRM data.
- Model event data into documented tables using SQL and dbt or Dataform; orchestrate jobs with Composer, Cloud Functions, Cloud Run or similar.
- Set up data quality tests and monitoring, and work with tagging specialists to validate GTM and GA4 implementations.
- Analyze GA4 export data, including event parameters, sessions and attribution, and translate measurement plans into metrics and tables.
Analysis, reporting and AI
- Answer client questions with SQL, including funnel drop-off, channel performance and customer lifetime value.
- Build semantic layers for Looker Studio and Looker dashboards and present findings to stakeholders in plain language.
- Prepare and govern datasets for BigQuery Conversational Analytics, Gemini and agent-based tools.
- Develop proof-of-concept analytics tools such as natural-language querying, automated insight summaries and anomaly detection.
- Use AI coding assistants in the development workflow.
What you'll bring
- Strong SQL, including window functions, CTEs and nested or repeated-field queries.
- Hands-on BigQuery experience with partitioning, clustering and cost control, plus working knowledge of GA4 and its export schema.
- Experience building and scheduling Google Cloud pipelines using Composer, Dataform, dbt, Cloud Run or similar.
- Python skills for API extraction, transformations and light automation; Git version control and documentation habits.
- Able to explain data to non-technical people, including clients, and interested in applying AI to analytics work.
Technology stack
- Google Cloud, GA4, Google Tag Manager, BigQuery, Looker Studio and Google Marketing Platform.
- Data tools include SQL, Python, Git and dbt or Dataform; orchestration may use Cloud Composer (Airflow), Cloud Functions or Cloud Run.
- Advertising data may include Google Ads, DV360, Meta and CM360.
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