AI & Analytics Engineer - Freelance
About Monks
Monks is a global, digital-first marketing, technology, and creative consultancy operating at the intersection of creativity, media, data, and culture. In APAC, our 700-strong team spans 14 offices across 11 countries, connected by a single, unified operating model.
As pioneers in the AI economy, we live an AI-first culture internally while helping enterprise clients shift from manual workflows to AI-native orchestration — scaling custom agent solutions (Monks.Flow), AI-driven campaigns, and next-gen AI search capabilities. By connecting brand strategy, media, data, and emerging technology around the consumer, we build intelligent platforms and content ecosystems for the world's leading brands. We foster a diverse, equitable, and inclusive workplace where authentic collaboration fuels industry-changing work.
The Role
Monks is looking for an Analytics Engineer to build the data foundations our clients' marketing decisions run on. You will turn raw GA4, media and CRM data into modelled, trusted datasets in BigQuery for some of the region's biggest brands. You will also help us put AI to work on that data.
You will join the Data team in Sydney or Melbourne (hybrid) as a full time, permanent, mid-level hire. The team covers measurement strategy, tagging and implementation, data engineering, reporting and applied AI. Our stack is built on Google Cloud: GA4, Google Tag Manager, BigQuery, Looker Studio and the Google Marketing Platform. We are increasingly building agentic and Gemini-based tools on top of client data.
The ideal candidate has built pipelines and models on Google Cloud for marketing data, writes strong SQL and is comfortable explaining the results to clients. You will work on a mix of engagements. Some are short builds with a clear finish line. Others are long-running data products you will own and improve over time.
This role offers a huge opportunity for growth within our AUNZ team and APAC data team with clear channels of progression into leadership. You will work on enterprise brands across automotive, retail, financial services and higher education. You will also get early access to the AI tools we are building plus a say in how they evolve.
What You'll Do
Pipelines and modelling: build and maintain pipelines that bring GA4 exports, ad platform data (Google Ads, DV360, Meta, CM360) and client CRM data into BigQuery.
Model raw event data into clean, documented tables using SQL and dbt or Dataform.
Orchestrate jobs with Cloud Composer (Airflow), Cloud Functions or Cloud Run.
Set up data quality tests and monitoring so issues are caught before they reach a dashboard.
GA4 and measurement: work with GA4 BigQuery export schemas, unnesting event parameters, sessionising events and rebuilding attribution where the UI falls short.
Partner with our tagging specialists to check that GTM and GA4 implementations produce data the models can rely on.
Translate measurement plans into the tables and metrics that answer them.
Analysis and reporting: answer client questions directly with SQL, from funnel drop-off to channel performance to customer lifetime value.
Build the semantic layer behind Looker Studio and Looker dashboards so numbers match across reports.
Present findings to client and internal stakeholders in plain language.
AI: prepare and govern datasets for BigQuery Conversational Analytics, Gemini and agent-based tools.
Conceptualise and build PoC-level AI tools on client data such as natural language querying, automated insight summaries and anomaly detection.
Use AI coding assistants in your own workflow to ship faster with fewer errors.
What You'll Bring
You write strong SQL: window functions, CTEs and nested or repeated field queries without reaching for a reference.
You have hands-on BigQuery experience including partitioning, clustering and cost control.
You have working knowledge of GA4: the event model, the BigQuery export schema and how it differs from the GA4 interface.
You have built and scheduled pipelines on Google Cloud (Composer, Dataform, dbt, Cloud Run or similar).
You use Python for data work: API extraction, transformation scripts and light automation.
You use version control with Git and have a habit of documenting what you build.
You are comfortable explaining data to non-technical people, including clients.
You are interested in applying AI to analytics work, backed by something you have tried or built.
Experience with Google Tag Manager (client side or server side), Google Marketing Platform data (CM360, DV360, SA360), Vertex AI, Gemini APIs or LLM-based agents is a big plus in consideration.
Exposure to privacy and consent topics such as Consent Mode, first-party data and the Australian Privacy Act is welcome, as are Google Cloud certifications (Professional Data Engineer or similar).
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