Live Nation Entertainment is the world’s leading live entertainment company, and they are seeking a Test Data Engineering Manager to lead a team focused on building scalable, automated data testing solutions. The role involves partnering with stakeholders to define data validation requirements and establishing reusable testing frameworks across the organization.
Responsibilities:
- Design and build reusable data quality frameworks integrated into Databricks pipelines
- Develop standardized validation libraries (schema checks, freshness, volume, anomaly detection)
- Define and enforce data quality standards and 'Definition of Done' across pipelines
- Build scalable solutions for synthetic data generation and masking
- Develop replay frameworks for validating pipeline changes against production scenarios
- Create automated regression testing harnesses for batch and streaming pipelines
- Establish monitoring, alerting, and SLA/SLO frameworks for data pipelines
- Build tools to measure and track data quality, pipeline health, and reliability metrics
- Enable proactive detection of data issues in production environments
- Lead and grow a team of data quality engineers and test data engineers
- Partner with Data Engineering, Product, and Analytics teams to embed quality practices
- Drive adoption of frameworks and standards across global engineering pods
- Define and execute a long-term roadmap for enterprise data quality
- Prioritize initiatives across multiple stakeholders and global teams
- Eliminate manual validation processes through automation and engineering best practices
Requirements:
- 5+ years in Data Engineering, Test Data Engineering, or related fields
- 2+ years in a technical leadership or management role
- Strong experience with Databricks, Spark, distributed data systems, Python and SQL
- Experience building automated validation or data quality frameworks
- Hands-on with data observability or validation tools (e.g., Great Expectations, Deequ, Soda)
- Familiarity with streaming architectures and real-time validation
- Solid understanding of anomaly detection and large-scale data validation patterns (e.g., hash/Merkle-based validation), and/or major TDM tools for data profiling and sampling
- Comfortable juggling multiple concurrent projects and setting priorities
- Experience with JIRA / agile user story and acceptance criteria writing
- Willingness to work with cross-functional teams across time-zones and odd hours as necessary
- Excellent analytical skills required, experience with user behavior data will be a leg up
- Track record of success launching test data solutions or BI validation applications
- Versatile, hands-on mindset with a bias for execution
- Optimism with drive, drive, drive
- AI orchestration experience a huge plus; ability to automate test data practices such as synthetic data generation, data profiling, and pipeline regression testing
- Passion for live music and events is a plus