About
Global operates in broadcast media production and distribution. Its Global:IQ platform supports AI-driven products and audience intelligence.
Responsibilities
•Design, build, and maintain scalable batch and near real-time data pipelines across ingestion, transformation, and serving layers
•Develop reusable data models and optimize pipeline performance, reliability, and cost
•Shape the Global:IQ data platform through best practices in architecture, tooling, CI/CD, and infrastructure as code
•Create reusable components and maintain clear technical documentation
•Implement data validation, testing, lineage, and observability
•Support governance and privacy-conscious data handling
•Partner with Data Science, MLOps, Product, and commercial teams to deliver production-ready data solutions
•Support and mentor others and communicate with stakeholders
•Take responsibility for production-grade data systems powering targeting, optimization, and measurement
•Onboard key datasets with robust ingestion and quality standards
•Deliver reliable pipelines supporting live production use cases
•Establish or improve data engineering standards and best practices
•Build working relationships across Data, Product, and commercial teams
•Identify opportunities to improve scalability, reliability, and efficiency
Requirements
•Strong Python and SQL skills
•Experience building production-grade data pipelines
•Hands-on experience with modern data tools such as Snowflake, Airflow, and dbt
•Knowledge of CI/CD, testing, version control, and infrastructure as code
•Understanding of observability, validation, and maintaining reliable data systems
•Ability to translate business and data science needs into scalable solutions and communicate clearly with stakeholders
•Pragmatic, ownership-driven, and curious approach, with a passion for building impactful data products
Nice to have
•Experience with cloud environments, preferably AWS
Conditions
Not specified in the posting.
