Project Overview

We are seeking an experienced data engineer to design and build a foundational marketing data platform that will ingest, standardise and consolidate data from digital marketing channels and agency sources. This is a strategic initiative for a forward-thinking marketing organisation seeking to establish a unified, scalable data infrastructure that will enable advanced analytics, marketing performance measurement, and multi-touch attribution modelling in the future.

You will own the end-to-end architecture and delivery of automated data pipelines, ETL/ELT frameworks, and a standardised common data model that integrates Google platforms, Meta, other digital advertising systems, and agency-provided datasets. Success will be measured by the reliability and quality of ingested data, the scalability of the platform to support multiple refresh cadences (daily, weekly, monthly), and its readiness to fuel downstream marketing analytics and attribution initiatives.

Key Activities

• Data Ingestion & Integration: Build and maintain automated data ingestion pipelines from Google marketing platforms, Meta, other digital advertising systems, and agency sources; design API-based integrations and manage connector maintenance.
• ETL/ELT Architecture: Design and implement scalable ETL/ELT frameworks and orchestration workflows capable of handling multiple refresh frequencies and varying data volumes.
• Data Modelling & Standardisation: Develop a unified, common data model that standardises disparate source data; create comprehensive data catalogues and documentation to support stakeholder adoption.
• Data Quality & Governance: Implement data quality rules, monitoring frameworks, and alerting to ensure data accuracy and reliability; establish governance standards for the platform.
• Transformation & Enrichment: Engineer data transformation and enrichment processes that prepare marketing data for analytics and attribution use cases.
• DevOps & Production Readiness: Establish CI/CD pipelines, implement infrastructure-as-code practices, and ensure production-ready deployment and ongoing platform reliability.

Your Background

Essential:

• 7+ years of professional data engineering experience, with demonstrated expertise in designing and maintaining production data platforms.
• Strong SQL proficiency, including query optimisation and performance tuning.
• Hands-on experience with Python for data processing and pipeline development.
• Proven experience building API-based integrations and working with third-party data sources.
• Demonstrable experience with cloud-based data platforms, particularly BigQuery and Google Cloud Storage.
• Solid experience in data modelling, ETL/ELT orchestration, and CI/CD practices.

Desirable:

• Prior experience building or enhancing marketing data platforms or customer data infrastructure.
• Hands-on familiarity with Google Ads, GA4, Meta, or Adobe data and APIs.
• Background in customer analytics, marketing attribution, or campaign performance reporting.
• Experience with data orchestration tools such as Airflow, dbt, or Dataflow.