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

SUMMARY

We’re looking for a talented Data Engineer to join our Data team and spread the power of Wiz.  The Data team develops and maintains the infrastructure for internal data and product analytics. We are looking for data enthusiasts, independent, logical thinkers with a can-do approach and a passion for problem-solving. We run a SaaS-based stack using BigQuery, Snowflake and dbt.

WHAT YOU'LL DO

• Design, build, and maintain data pipelines, datasets and catalogs for fast-growing products and business groups.
• Develop self-service data analytics solutions and infrastructure.
• Support ad hoc needs and requests of internal stakeholders.
• Collaborate with analysts, engineers, and internal customers from Product, Finance, Revenue, and Marketing.

WHAT YOU'LL BRING

• Bachelor’s or Master’s degree in a relevant technical field, or equivalent hands-on experience in software development or DevOps.
• 3+ years of experience working as a Data Engineer, including end-to-end designing, orchestrating, and building cloud-based data pipelines (e.g., Airflow, Prefect, Dagster).
• 3+ years of experience with dimensional data modeling and data warehouse implementation, specifically MPP databases like BigQuery, Snowflake, and Redshift.
• Strong knowledge of Python and Python-based data analysis tools such as Jupyter Notebooks and pandas.
• Strong SQL writing skills. Ability to write highly performant queries.
• Strong track record of executing projects independently in dynamic environments.
• Fast understanding of data and business needs and ability to translate them into data models.
• Team player with excellent communication skills.
• Containerization (Docker): Essential for reproducible environments.
• Knowledge of software engineering best practices: CI/CD concepts, code reviews, and unit testing.

ADVANTAGE

• Production-level experience with dbt, including project design, transformation, testing, and documentation.
• Infrastructure-as-Code (Terraform): Managing cloud resources (S3 buckets, IAM roles) via code.
• CI/CD pipelines (GitHub Actions/Jenkins): Automating the testing and deployment of data models.

By submitting your application, you acknowledge that Wiz will process your personal data in accordance with Wiz's Privacy Policy and that you consent to the retention of your application for consideration for future opportunities at Wiz.

We are looking for a senior, hands-on Product and Business Analyst to lead analytics within one of our core B2C app pods. This is not a reporting role. You will own the analytical direction of the pod, shape product decisions, and raise the bar on experimentation, rigor, and business impact.

You will work closely with Product, R&D, Monetization, and Marketing to drive onboarding, activation, retention, and revenue growth. The right candidate combines strong statistical depth with sharp business judgment and the ability to influence non-analytical stakeholders.

What You Will Own

Pod Performance Leadership

• Own core product KPIs across onboarding, activation, engagement, retention, and monetization
• Build and maintain a clear funnel view with defined breakpoints and drivers
• Proactively identify risks and growth opportunities, not just respond to requests
• Lead weekly and monthly business reviews with clear narratives and recommendations

Experimentation Excellence

• Lead end-to-end A B testing lifecycle: hypothesis design, sizing, guardrails, analysis, and decision framing
• Apply strong statistical thinking: power analysis, bias detection, novelty effects, false positives
• Partner with PM and R&D to improve instrumentation and experiment quality
• Ensure decisions are grounded in data and clearly translated into business tradeoffs

Data and Analytics Infrastructure

• Work deeply with SQL across large datasets including DBT
• Use Python for advanced analysis and experimentation workflows
• Operate across Databricks, Redshift, AWS environments
• Leverage Mixpanel and GrowthBook for behavioral analytics and experimentation
• Build scalable Tableau assets that drive self-serve and reduce ad hoc noise
• Define data quality standards in collaboration with Data Engineering

Stakeholder Influence and Cadence

• Translate complex analyses into simple, actionable stories
• Challenge vague assumptions and push for clarity in success metrics
• Create structure and consistency in how the pod uses data
• Raise the analytical standards across the team

Requirements

• 5+ years of experience in product or growth analytics in B2C, preferably mobile apps
• Deep experience with onboarding, activation, retention, churn, and LTV analysis
• Proven track record leading A B tests and influencing product decisions
• Strong SQL skills and high data intuition
• Experience with Python for analysis
• Experience working with experimentation platforms and behavioral analytics tools
• Ability to communicate clearly with senior stakeholders and cross-functional teams
• Independent, opinionated, and comfortable owning ambiguous problem spaces

Nice to Have

• Experience with monetization models: paywalls, pricing experiments, lifecycle incentives
• Experience building KPI monitoring and alerting frameworks
• Experience driving self-serve analytics adoption within product teams
• Exposure to applying AI or advanced modeling techniques to improve experimentation, personalization, or decision automation
• Experience with marketing analytics, including campaign performance analysis, attribution logic, channel efficiency, cohort quality, and translating acquisition data into retention and LTV insights

Who You Are

You think like a product owner but operate like an analyst.
You care about statistical rigor but know that speed matters.
You do not hide behind dashboards. You form opinions, challenge assumptions, and help the team decide what to do next.
You are comfortable being the analytical anchor of a pod and setting the standard for how decisions are made.

If you are excited about shaping product direction through data and leading analytics at a strategic level within a fast-moving B2C environment, we would love to meet you!

Data Engineer

We're hiring a Data Engineer to join our growing team of analytics experts in order to help & lead the build-out of our data integration and pipeline processes, tools and platform.

The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.

The right candidate must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.

In this role, you will be responsible for:

• Create ELT/Streaming processes and SQL queries to bring data to/from the data warehouse and other data sources.
• Establish scalable, efficient, automated processes for large-scale data analyses.
• Support the development of performance dashboards & data sets that will generate the right insight.
• Work with business owners and partners to build data sets that answer their specific business questions.
• Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision-making across the organization.
• Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
• Own the data lake pipelines, maintenance, improvements and schema.

About you:

• BS or MS degree in Computer Science or a related technical field.
• 3-4 years of Python / Java development experience.
• 3-4 years of experience as a Data Engineer or in a similar role (BI developer).
• 3-4 years of direct experience with SQL (No-SQL is a plus), data modeling, data warehousing, and building ELT/ETL pipelines - MUST
• Experience working with cloud environments (AWS preferred) and big data technologies (EMR,EC2, S3 ) - DBT is an advantage.
• Experience working with Airflow - big advantage
• Experience working with Kubernetes - advantage
• Experience working with at least in one of the big data environments: Snowflake, Vertica, Hadoop (Impala/Hive), Redshift etc - MUST
• Experience working with Spark - advantage
• Exceptional troubleshooting and problem-solving abilities.
• Excellent verbal/written communication & data presentation skills.

Why join Tipalti?

Tipalti is the AI-powered platform for finance automation, elevating how finance teams operate in the global economy. We empower our customers to scale faster and smarter by removing the complexities of doing global business and accelerating their finance operations efficiency. Our platform provides a comprehensive suite of finance automation solutions designed for mid-market businesses across accounts payable, global payouts, procurement, employee expenses, corporate cards, supplier management, tax compliance, and treasury. Tipalti partners with leading financial institutions such as Citi, Wells Fargo, J.P. Morgan, and Visa, enabling over 5,000 global companies to efficiently and securely pay millions of suppliers and payees across 200+ countries and territories, in 120 currencies.

At Tipalti, we pride ourselves on our collaborative culture, the quality of our product and the capabilities of our people. Tipaltians are passionate about the work they do, and keen to get the job done. Tipalti offers competitive benefits, a flexible workplace, career coaching, and an environment where diverse individuals can thrive and make an impact. Our culture ensures everyone checks their egos at the door and stands ready to reach for success together. 

Founded in Israel in 2010, Tipalti is a global business headquartered in the San Francisco Bay Area (Foster City) with offices in Tel Aviv, Plano, Toronto, Vancouver, London, Amsterdam, Tbilisi and Medellin.

Our tech teams are the engine behind our business. Tipalti’s tech ecosystem is extremely rich and we continually add new features to our products, ensuring that we respond to our clients’ needs at scale. Our tech teams retain a fast-paced, start-up vibe that encourages innovation and critical thinking. At Tipalti, you’ll have the opportunity to work with a diverse, global team of engineers, developers and product leaders who are collectively building the future of our best-in-class product suite as we transform financial operations for the future.

About Our Tel Aviv Offices:

Hybrid Work Model - Tipalti offers a hybrid work model, with two days per week working from home and three days per week from our beautiful offices in North Tel Aviv.

Shuttle Services - Shuttle services are available from the nearest train station and across Tel Aviv to the office.

Parking - Parking is available for all employees.

Snacks & Treats - Enjoy a selection of snacks and treats available on every floor.

#IL-hybrid

About The Support Team

Mixpanel Support is a team of talented problem-solvers from diverse backgrounds. We care deeply about helping our customers be successful and enabling them to get value from their data. We are located all over the world in San Francisco, Barcelona, London, and Singapore...

About The Role

The right candidate is an avid learner, an advocate for customers, and a collaborative teammate. The main responsibility of a Support Engineer is to help users solve technical challenges and use Mixpanel to make impactful product decisions. We’ve had team members focus on developing their technical skills to join the product and engineering teams, hone their customer-facing skills to become customer success managers or sales engineers, and take on leadership roles in the Support organization.

Responsibilities

The core responsibility of a Support Engineer is to support our customers at every turn in the Mixpanel journey by providing answers to product questions, sharing best practices, and debugging technical issues. You'll also develop your technical skills, collaborate with our Product team to improve our product, learn product analytics,s and mentor new team members.

• Become a Mixpanel product expert - you will help users understand our reports and features, help them use our APIs and SDKs, share best practices, and resolve account issues
• Respond to customer inquiries via Zendesk email, chat, Slack, and phone calls
• Investigate and document bugs and feature requests to share with our Product and Engineering teams
• Provide feedback regarding internal support processes, product functionality, and customer education resources to improve the customer experience
• Shape the product by regularly working closely with PM’s, engineers, and designers to incorporate customer learnings into change

We're Looking For Someone Who Has

• Experience providing customer facing SAAS support (in customer support, professional services, technical account management or similar)
• Ability to communicate technical concepts effectively in a clear, friendly writing style
• Excellent problem-solving and analytical skills
• Programming experience, understanding of web & mobile technologies,s and interacting with APIs
• Experience with debugging and collaborating with engineering to resolve complex technical issues, especially with JavaScript, Python, or mobile technologies
• Ability to be resourceful and resilient when faced with ambiguity and new challenges
• Dedication to developing expertise in a complex and constantly evolving product
• Interest and aptitude to develop technical skills and learn new technologies
• Experience providing SLA based support and/or dedicated support to strategic customers
• Speak Hebrew and fluent English

Bonus Points

• Experience with Mixpanel or other analytics tools
• Familiar with databases and cloud data warehouses like Google Cloud, Amazon Redshift, Microsoft Azure, Snowflake, Databricks, etc.
• Familiar with product analytics implementation methods like SDKs, Customer Data Platforms (CDPs), Event Streaming, Reverse ETL, etc.

About Kape Technologies

Kape is a cybersecurity company focused on helping everyone have a better digital experience with greater privacy and protection. With over 1000 experienced individuals across ten global locations, including the UK, Israel, Germany, Romania, France, the Philippines, USA, Singapore, Hong Kong, and Cyprus, the Kape team is guided by a single mission: to create a more secure and safe world.

Job Summary

We are seeking a highly skilled and hands-on Senior Data Engineer to architect and maintain modern data infrastructure and pipelines.

This is a technical role focused on building a scalable data platform that powers analytics, insights, and agentic workflows to enable data-driven decision making across the company. You will work closely with analysts, product, and engineering teams to design end-to-end data solutions using tools like AWS Redshift, Athena, Snowflake, and other leading cloud platforms.

Core Responsibilities

• Design and build scalable data pipelines to ingest, process, and store large volumes of structured and unstructured data from diverse sources. 
• Develop and maintain robust data warehouse architectures leveraging tools such as AWS Redshift, Athena, and Snowflake. 
• Optimize data models, queries, and storage strategies for performance, scalability, and cost-effectiveness. 
• Collaborate with cross-functional stakeholders (analytics, product, payments and finance) to gather requirements and deliver data solutions that support business goals. 
• Ensure data quality, security, and privacy through best practices in governance, testing, and monitoring. 
• Own and operate production data workflows, resolving incidents and ensuring reliability. 
• Develop and maintain infrastructure optimized for both analytics and AI workloads, including transformation and semantic layers.
• Design and monitor agentic flows aimed at democratizing data access for users across the company, ensuring reliability, scalability, and accuracy.

Tech Stack

• Languages & Tools: Python, SQL 
• Data Warehousing & Query Engines: Snowflake, AWS Redshift, Athena 
• Pipeline & Orchestration: Apache Airflow, AWS Glue, dbt 
• Cloud & DevOps: AWS (Lambda, S3, IAM), Docker, Terraform 
• Streaming: Kafka, Kinesis 
• BI & Analytics: Tableau, Power BI

Core Requirements

• Bachelor's or Master’s degree in Computer Science, Engineering, or related field
• 5+ years of experience as a Data Engineer, with a strong focus on data pipeline development and data warehousing
• Deep proficiency in Snowflake or AWS Redshift
• Strong programming skills in Python and SQL
• Hands-on experience building LLM-powered applications or workflows in a production environment for analytical use cases, for example ‘ask your data’ interfaces
• Experience with pipeline orchestration tools (Airflow, Glue, dbt)
• Solid understanding of data modeling, schema design, and ETL/ELT processes
• Strong analytical, problem-solving, and communication skills
• Ability to work cross-functionally and mentor others
• Experience in high-growth, product-led, or SaaS environments

Nice to Have

• Familiarity with AWS infrastructure and DevOps practices
• Knowledge of data privacy and security standards (GDPR, SOC2)
• Solid understanding of agent architectures (tool use, planning, memory management), prompt engineering and evaluation

Senior Data Engineer

About the Role

Token Security, a leading platform for Non-Human Identity (NHI) management, is seeking an experienced Senior Data Engineer to join our growing team. The ideal candidate will have deep expertise in building large-scale data pipelines, designing high-performance data stores, and enabling analytics on massive security datasets. This role will be key in shaping how we ingest, process, and analyze billions of identity and activity logs to deliver insights to our customers.

Responsibilities

• Collaborate closely with Product, Backend, and Security teams to transform raw data into customer-facing features and insights.
• Design, implement, and maintain scalable ETL/ELT pipelines to process large volumes of log and event data.
• Build and maintain data ingestion frameworks at scale.
• Ensure data quality, availability, and performance.
• Proactively monitor, troubleshoot, and improve data infrastructure to support rapid growth.
• Architect and optimize ClickHouse, PostgreSQL, and other data stores for fast queries and efficient aggregation.

Requirements

• 5+ years of experience in a Data Engineer role, with a track record of building and maintaining scalable backend systems.
• Strong communication skills, collaborative mindset, and a passion for building data-driven products.
• Proven track record with ETL/ELT pipelines and data pipeline frameworks.
• Proficiency in Python and experience working with large-scale backend systems.
• Strong hands-on experience with Data Warehouse (e.g., Redshift, BigQuery, Snowflake).
• In-depth experience of cloud platform services (AWS preferred).
• Bonus: experience with event streaming technologies (Kafka, Kinesis) or data orchestration tools (Airflow, dbt, Dagster).