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HeadГибридПолная занятость

VP, Head of Data Platform

Оценка ИИ

Высокий балл обусловлен статусом компании Payoneer как глобального лидера финтеха и масштабностью задач. Роль предлагает значительное влияние на стратегию компании и работу с передовым стеком технологий, хотя и предполагает высочайший уровень ответственности.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Это позиция высшего руководства, требующая более 15 лет опыта, включая управление командами от 40 человек и огромными бюджетами. Кандидат должен обладать как глубочайшей технической экспертизой в облачных данных (GCP, Snowflake), так и выдающимися навыками стратегического управления.

Анализ зарплаты

Медиана220 000 $
Рынок180 000 $ – 280 000 $
Оценка ИИ

Указанная роль VP в Израиле предполагает компенсацию выше среднего по рынку, учитывая масштаб компании Payoneer. Ожидаемый доход включает значительную базовую часть, бонусы и опционы (LTI).

Сопроводительное письмо

I am writing to express my strong interest in the VP, Head of Data Platform position at Payoneer. With over 15 years of experience in software engineering and a proven track record of leading large-scale data organizations, I am confident in my ability to drive Payoneer's data strategy forward. My background includes managing cross-functional teams of 40+ engineers and overseeing complex migrations to modern cloud-native architectures, which aligns perfectly with your current needs for scaling the data infrastructure.

Throughout my career, I have focused on building robust, real-time data streaming pipelines and implementing advanced data observability frameworks like Monte Carlo to ensure high reliability. I am particularly impressed by Payoneer's mission to connect underserved businesses to the global economy, and I am eager to apply my expertise in GCP, BigQuery, and Kafka to enhance your data products. I am a strong advocate for operational excellence and look forward to fostering a culture of technical innovation within your R&D tracks.

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Присоединяйтесь к лидеру финтех-индустрии и возглавьте трансформацию данных в глобальном масштабе!

Описание вакансии

About Payoneer

Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers, and partners in over 190 countries and territories.

By taking the complexity out of the financial workflows–including everything from global payments and compliance to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence.

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.

**#LI-Hybrid

#LI-CA1**

The Payoneer Ways of Working 

Act as our customer’s partner on the inside

Learning what they need and creating what will help them go further. 

Do it. Own it.

Being fearlessly accountable in everything we do. 

Continuously improve

Always striving for a higher standard than our last. 

Build each other up 

Helping each other grow, as professionals and people. 

If this sounds like a business, a community, and a mission you want to be part of, apply today.

We are committed to providing a diverse and inclusive workplace. Payoneer is an equal opportunity employer, and all qualified applicants will receive consideration for employment no matter your race, color, ancestry, religion, sex, sexual orientation, gender identity, national origin, age, disability status, protected veteran status, or any other characteristic protected by law. If you require reasonable accommodation at any stage of the hiring process, please speak to the recruiter managing the role for any adjustments. Decisions about requests for reasonable accommodation are made on a case-by-case basis.

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Навыки

  • GCP
  • BigQuery
  • Snowflake
  • Databricks
  • Redshift
  • Kafka
  • dbt
  • Spark
  • Kubernetes
  • Terraform
  • Dataflow
  • Looker
  • Tableau
  • Power BI
  • Monte Carlo

Возможные вопросы на собеседовании

Проверка опыта управления крупными подразделениями и ресурсами.

Опишите ваш опыт управления инженерной организацией численностью более 30 человек: как вы выстраивали структуру и процессы делегирования?

Оценка технического видения и способности проводить масштабные изменения.

Каков был ваш самый сложный проект по миграции или трансформации платформы данных, и как вы обеспечивали непрерывность бизнеса в процессе?

Проверка фокуса на надежность данных, что критично для финтеха.

Как вы внедряли процессы операционного совершенства и мониторинга (Data Observability) для минимизации инцидентов в данных?

Оценка навыков взаимодействия с бизнесом.

Как вы приоритизируете задачи в дорожной карте платформы данных, когда сталкиваетесь с конфликтующими требованиями от разных бизнес-юнитов?

Проверка лидерских качеств и развития талантов.

Каков ваш подход к найму и удержанию топовых инженеров данных в условиях высокой рыночной конкуренции?

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