Job Description
We are on the lookout for aSenior Engineering Manager, Data Engineering to lead the Data Engineering Domain within Global Discovery. This is a high-impact leadership role where you will manage three distinct but interconnected squads responsible for the data platform and real-time ingestion.
You will be the custodian of the critical data foundation that powers our Search & Recommendation engines—the "brain" of our user experience—and enables business insights across the entire organization. If you are passionate about orchestrating complex pipelines, building high-throughput real-time systems, and establishing a culture of data trust at a global scale, we want to hear from you.
As a Senior Engineering Manager, you will lead a domain responsible for the unified data platform that drives our Tier-1 discovery services.
1. Lead & Scale: Manage and mentor a diverse group of engineers and managers across three squads. Develop a strong delegation framework and foster a culture of technical excellence and ownership.
2. Build a Unified Data Platform: Orchestrate complex data pipelines across both Batch (Airflow, dbt, BigQuery) and Streaming ecosystems. Ensure seamless integration between raw data ingestion and downstream consumption by Data Science models and Analytics use-cases.
3. Ensure Real-Time Reliability: Lead the Backend team responsible for high-throughput real-time ingestion services that feed Search and Recommendation use cases. You will ensure low-latency processing and high availability for these critical systems.
4. Champion Data Quality & Governance: Establish a culture of data trust. Improve automated data quality monitoring and define clear SLAs for data freshness and accuracy for both analytical and operational use cases.
5. Empower Data Science & Analytics: Act as a strategic partner to the Data Science and Analytics teams. Provide them with high-reliability datasets, clean architecture, and efficient self-service tooling (Cosmos, dbt) to accelerate model training and insight generation.
6. Drive Strategy: Translate tribe-level goals into a comprehensive 18-month technical roadmap. Bridge the gap between Data Science needs, Product requirements, and Engineering constraints.
Qualifications
We are looking for a candidate with proven architectural excellence and deep leadership experience.
7. M2 Leadership Experience: You have several years of experience managing managers and leading multiple diverse squads (, managing both Data Engineers and Backend Engineers).
8. Proven Architectural Excellence: You have a track record of architecting and building robust data platforms from the ground up. You have made high-stakes architectural decisions that ensured platform reliability and cost efficiency at scale.
9. Advanced Data Stack Expertise: You possess deep expertise in designing modern data platforms on cloud infrastructure (GCP/AWS). You are proficient with our stack: Python, Airflow, dbt, BigQuery, Kubernetes, and Streaming technologies (Kafka/Flink/Spark).
10. Backend & Distributed Systems Knowledge: You have a strong understanding of real-time backend systems and high-scale APIs to effectively guide the ingestion team. You understand the trade-offs in distributed systems and have already been responsible for such systems at a global scale.
11. Stakeholder Management: You excel at managing expectations and bridging the gap between technical constraints and business needs, working closely with Product Managers and Data Scientists.