What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Prior experience in a data operations or data engineering roles with experience working in a cloud-based data warehouse environment (Snowflake preferred)
- Understanding of data warehouses and operations including user management and experience in implementing and enforcing data governance policies and procedures
- Proficiency in SQL for data querying, manipulation, and performance tuning
- Experience with JIRA or similar project management tools
- Proven track record of working with Engineering/Scrum teams to deliver on operations needs
- Experience working with data onboarding (LiveRamp preferred) and 1PD
- Excellent communication skills, with the ability to effectively communicate technical concepts to non-technical stakeholders
- Strong understanding of the product development life cycle and product management processes
- Proven track record of delivering data driven solutions with a customer-first mindset
- Self-driven, motivated, and purpose-led individual
- Great understanding on data and the ability to use data to inform decision-making and prioritization.
- Great understanding on Agile methodology
- Excellent verbal and written communication.
- Prior project management experience is preferred.
Nice to have
- Experience in Media
- Experience in Advertising
Day to day
- You will oversee the day-to-day management of our Kinesso Audience Solutions (KAS) data warehouse and ensure its integrity, scalability, and efficiency in collaboration with the data engineering team.
- Investigate and resolve data-related issues and incidents in a timely manner, collaborating with cross-functional teams as needed.
- Oversee the management and maintenance of our audience data infrastructure, including data pipelines, data warehousing, and ETL processes.
- Implement and enforce data governance policies and procedures to ensure data integrity, security, and compliance with requirements.
- Maintain comprehensive documentation of data infrastructure and processes as well as training users on best practices of how to use KAS.
- Lead the implementation of changes and enhancements to the data infrastructure, following change management best practices.