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We are seeking a seasoned and execution driven VP, head of data platform to lead all the R&D tracks of the Data and Analytics organization. This role focuses on leading a complex data engineering organization at scale, driving delivery, operational excellence and cross-company enablement through world-class data platforms and tools.
This leader will serve as the engineering owner of our data platform, managing multiple data infra, data engineering and BI development teams, overseeing extensive resources, and ensuring the delivery of high-quality, scalable, and reliable data products and services. This position requires a strong technical background combined with exceptional leadership, strategic thinking, and cross-functional collaboration skills.
He will also act as a key stakeholder in defining the architecture and strategic direction of our data infrastructure, pipelines, AI/ML infra and platforms to support the company's rapid growth and evolving business needs.
Hybrid
Full-time
What youll do: 
Lead and manage the entire data platform, including:
Real-Time Data & Streaming Infrastructure: Introduce and engineer robust data streaming infrastructures (e.g., using Kafka, Pub/Sub, Dataflow) to enable near-real-time data ingestion and scalable low-latency data serving, unlocking advanced analytics and critical use cases.
Data engineering teams responsible for the data ingestion, transformation and delivery pipelines
BI infra and development teams owning the cross-company consumption layer, including BI tools, BI data layers and dashboards
Serve as the operational and delivery lead across the data platform, ensuring strong project execution, roadmap alignment and measurable business impact
Data Engineering & Architecture Oversight: Lead the design, development, and evolution of scalable data platforms, encompassing data lakes, data warehouses, and advanced data products, ensuring they meet performance, reliability, and business requirements.
Operational Excellence & Reliability: Establish and drive engineering operational excellence processes across data engineering, significantly improving data quality, availability, and system reliability. Implement frameworks for proactive monitoring, alerting, and incident management, reducing major incidents and ensuring continuous visibility into data flows.
Advanced Data Observability: Integrate and leverage cutting-edge data observability solutions (e.g., Monte Carlo) to provide comprehensive visibility into data pipelines, enabling proactive detection and resolution of anomalies.