Description
Key Skills: Java, Spring Boot, ClickHouse, OpenSearch, Logstash, AWS, SQL, ETL, Spark, Grafana
Good to Have Skills: Experience in digital measurement, panel management, or attribution ecosystems. Knowledge of Connected TV (CTV) platforms and streaming data collection. Familiarity with privacy-compliant, software-first measurement solutions. Hands-on experience with Databricks. Advanced knowledge of ElasticSearch, MDL, Lambda, S3, and EC2 services.
Roles & Responsibilities:
- Lead and mentor high-performing engineering teams, fostering a culture of technical excellence, automation, and continuous improvement.
- Own the Tech Roadmap and long-term planning for data engineering workstreams, ensuring alignment with product goals and business efficiency initiatives.
- Partner closely with Product Management and Data Science to define system requirements for automated panel data processing and eligibility.
- Manage resource bandwidth and prioritize quarterly planning integrity over ad-hoc requests to ensure project delivery.
- Oversee the architecture and scaling of data pipelines using technologies like Spring Boot, ClickHouse, OpenSearch, and Logstash.
- Drive the transition toward automated, longitudinal data processing to replace deterministic manual processes.
- Ensure robust data validation across complex event streams, batch jobs, and downstream reporting dashboards.
- Implement rigorous performance standards and tech excellence line items, such as Cloud Cost Optimization and SEV-1 Reduction targets.
- Resolve critical technical blockers related to data schemas, device-process date misalignment, and international market integrations.
- Implement and oversee ETL job monitoring and performance optimization for critical data pipelines.
Experience Required: 12+ years of relevant experience with proven experience managing engineering teams in an Agile environment with focus on roadmap visibility and stakeholder communication