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

Key Skills

Education

Any Graduate