Key Responsibilities

• Build and maintain automated data ingestion pipelines.

• Integrate data from:

• Google marketing platforms

• Meta platforms

• Other digital advertising systems

• Agency-provided datasets and reports

• Design scalable ETL/ELT frameworks.

• Standardise data from disparate sources into a common data model.

• Manage varying refresh frequencies (daily, weekly, monthly).

• Develop data quality rules and monitoring.

• Implement data transformation and enrichment processes.

• Support future analytics initiatives including marketing performance measurement and MMM readiness.

Mandatory Skills

• 7+ years data engineering experience.

• Strong SQL expertise. Query optimization.

• Python for data processing.

• Experience building API-based integrations.

• Experience with cloud-based data platforms (BigQuery & Cloud Storage preferred).

• Data modelling experience.

• ETL/ELT orchestration experience.

• CI/CD and DevOps familiarity.

• Experienced in analyse with Google Ads, GA4, Meta and DV360 (with GA4 being the strongest preference.

• Higher focus on Marketing analytics experience and exposure to GCP, lower focus on strong engineering experience

• Banking industry experience

• Having AI skills and are comfortable with adoption of AI (not expected to be experts but would need to know how to use it).

Preferred Skills

• Marketing data platform experience.

• Customer analytics exposure.

• Marketing attribution and campaign reporting knowledge.

Deliverables

• Automated ingestion framework.

• Unified marketing data model.

• Data catalogue and documentation.

• Production-ready data pipelines.

• Data quality framework.