VP, Head of Data Platform

Role summary:

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 in Payoneer. 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 you’ll 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.
• Cross-functional Collaboration & Stakeholder Management: Collaborate extensively with product, analytics, business, and infrastructure teams to align data strategies with overarching business priorities, ensuring the delivery of high-quality data products that meet diverse user needs.
• Innovation & Technology Adoption: Stay abreast of the latest data, cloud, and AI trends, driving the evaluation and adoption of modern cloud-native technologies to continuously improve platform capabilities and future-proof the ecosystem.
• Leadership & Team Growth: Lead, mentor, and grow a large team of data engineers, fostering a culture of technical excellence, continuous learning, and agile methodologies. Oversee budget management and drive talent development within the team.
• Data Governance & Quality: Oversee the implementation of standards for data quality, data integrity tools, governance, privacy, and regulatory compliance across the data ecosystem.

Who you are? 

• Extensive Experience: 15+ years of progressive experience in the software industry, with a significant portion in data engineering, data platform design, and leadership roles.
• 5+ in senior R&D or VP-level roles, managing large cross-functional teams. Proven experience in leading and managing large engineering teams (e.g., 30-40+ engineers) and overseeing large budgets.
• Deep Technical Expertise-
• Profound knowledge of modern cloud data platforms such as GCP, BigQuery, Snowflake, Databricks, Redshift, and Bigtable.
• Hands-on experience with ETL/ELT tools and frameworks (e.g., DBT, Dataform, Spark).
• Strong familiarity with real-time data processing and streaming platforms (e.g., Kafka, Pub/Sub, Flink, Dataflow, Kafka Streams, Storm).
• Experience with data warehousing, data lakes, Hadoop ecosystems (e.g., Cloudera)
• Experience in BI domains tools (e.g., Looker, Tableau, Power BI)
• Familiarity with legacy ecosystem (MySQL, SSRS)
• Experience with containerization and orchestration technologies like Kubernetes and infrastructure-as-code tools like Terraform.
• Operational Excellence: Demonstrated ability to establish and improve operational excellence processes, including proactive monitoring, alerting, incident management, and data observability solutions.
• Strategic & Business Acumen: Strong business acumen and the ability to align technical decisions with strategic business goals.
• Communication & Collaboration: Excellent communication, stakeholder management, and cross-functional collaboration skills to effectively align diverse teams and stakeholders.
• Problem-Solving: Exceptional problem-solving abilities and a creative approach to technical challenges.
• Education: Bachelor of Science degree, preferably in Computer Science or a related technical field.

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