Job Description

Job Summary

The Data Engineer will design, build, and maintain scalable data pipelines, data models, and cloud-based infrastructure supporting Content Management capabilities. The role contributes to Content Insights, AI-enabled use cases, and DAM data layers, ensuring a sustainable data foundation aligned with business objectives and transformation goals.

Key Responsibilities

Data Engineering & Pipeline Development

• Design, build, and maintain reliable data pipelines for CMS, DAM, and Content Insights platforms.
• Develop ETL/ELT workflows to ingest, transform, and distribute data efficiently.
• Ensure scalability, performance, and reliability of data processing systems.

Data Modelling & Architecture

• Create and maintain data models supporting analytics and AI/ML use cases.
• Structure datasets for Content Insights, DAM reporting, and AI pipelines.
• Ensure consistency, reusability, and maintainability of data structures.

Cloud Platform (GCP)

• Develop and manage data solutions on Google Cloud Platform (GCP).
• Work with BigQuery and data pipeline tools to store and process large datasets.
• Maintain performance and scalability of cloud data infrastructure.

Data for AI & Insights

• Support data needs for content insights, analytics, and AI-enabled capabilities.
• Enable datasets for image classification, ratings & reviews, and user-generated content analysis.
• Collaborate with Data Scientists and MLEs to support machine learning workflows.

Data Quality & Governance

• Ensure data quality, accuracy, and integrity across pipelines and systems.
• Implement monitoring, validation, and governance practices.
• Support sustainable and maintainable data architecture.

Cross-functional Collaboration

• Collaborate with Product Owners, Engineers, Data teams, and stakeholders.
• Support cross-functional initiatives across Growth & Marketing and related domains.
• Contribute to Agile delivery cycles and team objectives.

Skill Requirements

Required Skills & Experience

• Strong experience with Python and SQL.
• Experience with BigQuery, dbt, and GCP.
• Hands-on experience in data pipeline development and data modelling.
• Understanding of ETL/ELT processes and data warehousing.
• Experience in Agile and cross-functional environments.
• Business-level English communication skills.

Preferred / Nice-to-Have Skills

• Experience with AI/ML pipelines and data for analytics.
• Knowledge of CMS/DAM ecosystems or marketing data platforms.
• Experience with large-scale data systems and cloud architectures.

Other Requirements

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