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

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!

At Databricks, our core values are at the heart of everything we do. Our culture of proactiveness and a customer-centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user-friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement.

You will be an essential part of this mission, using your technical expertise to demonstrate how our Data and Intelligence Platform can help customers solve their complex data challenges.

You'll work with a collaborative, customer-focused team that values innovation and creativity. You'll use your skills to create customized solutions to help our customers achieve their goals and guide their businesses forward.

Join us in our quest to change how people work with data and make a better world!

The impact you will have:

• Form successful relationships with clients throughout your assigned territory, providing technical and business value to Databricks customers in collaboration with Account Executives.
• Operate as an expert in big data analytics to excite customers about Databricks. You will develop into a ‘champion’ and trusted advisor on multiple issues of architecture, design, and implementation to lead to the successful adoption of the Databricks Data Intelligence Platform.
• Scale best practices in your field and support customers by authoring reference architectures, how-tos, and demo applications, and help build the Databricks community in your region by leading workshops, seminars, and meet-ups.
• Grow your knowledge and expertise to the level of a technical and/or industry specialist.

What we look for:

• Engage customers in technical sales, challenge their questions, guide clear outcomes, and communicate technical and value propositions.
• Passion for delivering technical propositions, identifying customers' pain points and explaining essential areas for business value to develop a trusted advisor skillset.
• Knowledgeable in a core Big Data Analytics domain with some exposure to advanced Data Engineering and/or Data science use cases.
• Experience diving deeper into solution architecture and expertise with at least one major public cloud platform.
• Code in a core programming language like Python, Java, or Scala.
• A foundational understanding of Apache Spark™ architecture is preferable; hands-on skills will benefit the role.

Notes on mandatory requirements:

• Flexibility to travel (up to 20-30% as required for customer meetings, events, and training).
• Business proficiency in Hebrew and English is required. Fluency in additional regional languages may be advantageous.

Job Summary

We're looking for a Data Analyst to join one of our R&D. You'll design and deliver data-driven solutions that combine data analysis, statistical methods, improved heuristics, and ML models training to power Beamup's autonomous supply chain intelligence platform. You'll work closely with data science, engineering, product, and supply chain experts — owning solutions from problem definition to iterative improvement.

Responsibilities

• Analyze large, multi-source operational datasets to identify trends, anomalies, and drivers of supply chain performance
• Improve and maintain heuristic rules and analytical models for supply chain use cases (e.g., inventory risk, demand patterns, root-cause analysis)
• Train and iterate on ML models to enhance existing analytical solutions
• Define success metrics and evaluation plans with support from senior DS/PM; run error analysis
• Work with stakeholders to create and maintain ground truth (label definitions, labeling workflows, QA checks, feedback loops)
• Implement and refine hybrid decision logic by combining analytical outputs with statistical methods and SQL/rules-based logic for robustness and explainability
• Collaborate with software engineers to support deployment of analytical solutions, including testing and logging
• Monitor deployed models/rules, investigate performance issues (data quality, drift, edge cases), and iterate based on outcomes
• Contribute to team practices: reproducible notebooks/code, documentation, and experiment tracking

Requirements

• BSc in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field (or equivalent practical experience)
• 2+ years of experience as a Data Analyst in a product or business environment (or equivalent practical experience)
• Familiarity with Python and data analysis workflows
• Solid SQL skills (joins, aggregations, window functions) and comfort working with production data in a warehouse/lake environment
• Experience performing rigorous evaluation (baselines, cross-validation where relevant, error analysis)
• Ability to translate business questions into measurable metrics and a clear analytical plan (with guidance when needed)
• Experience working with messy real-world data: data validation, debugging pipelines, and collaborating on labeling/ground truth
• Strong communication and collaboration skills with engineering, product, and domain experts; comfortable receiving feedback and iterating fast

Nice to Have (Advantages)

• Experience building predictive ML models (e.g., classification, regression, anomaly detection)
• Familiarity with common DS libraries: pandas, NumPy, scikit-learn
• Experience with big data tools (e.g., Spark, BigQuery, Snowflake, Databricks)
• Experience with development AI agents (Cursor, Caude-Code, etc.)

We are looking for a visionary and technically versatile Data Science Manager to join the Data Science & MLE group within our DS & Analytics organization.

In this pivotal role, you will lead a hybrid team of Data Scientists and Machine Learning Engineers, acting as the bridge between cutting-edge technical innovation and high-level business strategy. You won't just be managing a team; you will be the Technical Lead defining how we solve complex problems-from predicting player behavior to optimizing marketing budgets using the latest in Generative AI.

You will partner closely with Game Directors, Product Managers, and our central analytics teams to drive value across Zynga's diverse portfolio. If you are a leader who is "bilingual" in data-possessing deep Data Science expertise to guide methodology while bringing high MLE and Engineering skills to build scalable, production-ready systems-we want to hear from you.

Key Responsibilities

• Team Leadership & Mentorship: Recruit, retain, and develop top-tier talent within the Data Science & MLE team. Foster an inclusive culture of innovation where technical rigor meets creative problem-solving.

• Technical Direction & Engineering Standards: Act as the hands-on Technical Lead for the domain. You will supervise the end-to-end development lifecycle-from research to production-enforcing high standards and MLOps to ensure our models are scalable and maintainable.

• Strategic DS & Analytics Support: Drive the development of advanced analytical frameworks to solve core business challenges. You will guide the team in applying rigorous statistical and machine learning methods to areas such as Time Series Forecasting, Causal Inference, Marketing Optimization, Root Cause Analysis, and more.

• Strategy & Collaboration: Partner with Game Directors, BI Platform PMs, and embedded analytics teams to define the data strategy and roadmap. You will ensure that our technical initiatives are directly aligned with company-wide goals and solving the right problems.

• Global Alignment: Maintain a tight collaborative network with Data Science & Analytics managers in North America, ensuring global consistency in methodologies, knowledge sharing, and joint development.

Required Qualifications

• Experience: 5–10 years of experience in data science or machine learning roles, with 3+ years of experience in people management.

• Technical Proficiency: Expert proficiency in SQL and Python. You must be capable of writing and reviewing production-grade code and have hands-on experience with cloud environments (GCP, AWS, Databricks).

• Modeling Expertise: Strong background in Classical ML, Deep Learning, and familiarity with Generative AI (LLMs, Multimodal embeddings, Langchain or like technologies).

• Engineering Mindset: Proven ability to bridge the gap between Research and Engineering. Experience deploying models to production and maintaining them is essential.

• Education: Master’s degree in Computer Science, Math, Statistics, or a related quantitative field; a PhD is strongly preferred.

Preferred Qualifications

• Experience in the mobile gaming industry or high-velocity B2C tech environments.

• Passion for gaming and experience playing various game genres.

• Familiarity with modern data platforms (e.g., Vertex AI, Cloud Run, Sage).

What You'll Need to Succeed

• Independence & Proactivity: Ability to operate in a fast-paced, dynamic environment, managing timelines and mitigating risks effectively.

• Data-Driven Storytelling: Fluent English is mandatory. You need the ability to translate complex data science concepts into clear, compelling narratives for non-technical stakeholders to influence decision-making.

• Collaborative Spirit: A willingness to work across borders and time zones, partnering effectively with teams in Tel Aviv and North America.

We are looking for a visionary and technically versatile Data Science Manager to join the Data Science & MLE group within our DS & Analytics organization.

In this pivotal role, you will lead a hybrid team of Data Scientists and Machine Learning Engineers, acting as the bridge between cutting-edge technical innovation and high-level business strategy. You won't just be managing a team; you will be the Technical Lead defining how we solve complex problems-from predicting player behavior to optimizing marketing budgets using the latest in Generative AI.

You will partner closely with Game Directors, Product Managers, and our central analytics teams to drive value across Zynga's diverse portfolio. If you are a leader who is "bilingual" in data-possessing deep Data Science expertise to guide methodology while bringing high MLE and Engineering skills to build scalable, production-ready systems-we want to hear from you.

Key Responsibilities

• Team Leadership & Mentorship: Recruit, retain, and develop top-tier talent within the Data Science & MLE team. Foster an inclusive culture of innovation where technical rigor meets creative problem-solving.

• Technical Direction & Engineering Standards: Act as the hands-on Technical Lead for the domain. You will supervise the end-to-end development lifecycle-from research to production-enforcing high standards and MLOps to ensure our models are scalable and maintainable.

• Strategic DS & Analytics Support: Drive the development of advanced analytical frameworks to solve core business challenges. You will guide the team in applying rigorous statistical and machine learning methods to areas such as Time Series Forecasting, Causal Inference, Marketing Optimization, Root Cause Analysis, and more.

• Strategy & Collaboration: Partner with Game Directors, BI Platform PMs, and embedded analytics teams to define the data strategy and roadmap. You will ensure that our technical initiatives are directly aligned with company-wide goals and solving the right problems.

• Global Alignment: Maintain a tight collaborative network with Data Science & Analytics managers in North America, ensuring global consistency in methodologies, knowledge sharing, and joint development.

Required Qualifications

• Experience: 5–10 years of experience in data science or machine learning roles, with 3+ years of experience in people management.

• Technical Proficiency: Expert proficiency in SQL and Python. You must be capable of writing and reviewing production-grade code and have hands-on experience with cloud environments (GCP, AWS, Databricks).

• Modeling Expertise: Strong background in Classical ML, Deep Learning, and familiarity with Generative AI (LLMs, Multimodal embeddings, Langchain or like technologies).

• Engineering Mindset: Proven ability to bridge the gap between Research and Engineering. Experience deploying models to production and maintaining them is essential.

• Education: Master’s degree in Computer Science, Math, Statistics, or a related quantitative field; a PhD is strongly preferred.

Preferred Qualifications

• Experience in the mobile gaming industry or high-velocity B2C tech environments.

• Passion for gaming and experience playing various game genres.

• Familiarity with modern data platforms (e.g., Vertex AI, Cloud Run, Sage).

What You'll Need to Succeed

• Independence & Proactivity: Ability to operate in a fast-paced, dynamic environment, managing timelines and mitigating risks effectively.

• Data-Driven Storytelling: Fluent English is mandatory. You need the ability to translate complex data science concepts into clear, compelling narratives for non-technical stakeholders to influence decision-making.

• Collaborative Spirit: A willingness to work across borders and time zones, partnering effectively with teams in Tel Aviv and North America.

ABOUT PLACER.AI: 

Placer.ai is transforming how organizations understand the physical world. Our location analytics platform provides unprecedented visibility into locations, markets, and consumer behavior. Placer empowers thousands of customers—from Fortune 500 companies, to local governments and nonprofits— to make smarter, data-driven decisions.

What sets us apart? We've built the most advanced location intelligence platform in the market while maintaining an uncompromising commitment to privacy, proving that powerful analytics and responsible data practices can coexist.

Our growth reflects the market's demand: we reached $100M in annual recurring revenue within just 6 years of launching, achieved unicorn status with a $1B+ valuation in 2022, and continue to expand rapidly as one of North America's fastest-growing tech companies. We're creating a $100B+ market opportunity, and we're just getting started.

Named one of Forbes America's Best Startup Employers and a Deloitte Technology Fast 500 company, we're building a culture where innovation thrives, collaboration is the norm, and every team member contributes to reshaping how the world understands location.

WHY JOIN PLACER.AI? 

• Join a rocketship! We are pioneers of a new market that we are creating
• Take a central and critical role at Placer.ai
• Work with, and learn from, top-notch talent
• Competitive salary
• Excellent benefits
  
  

NOTEWORTHY LINKS TO LEARN MORE ABOUT PLACER 

• Placer.ai's $100M round C funding (unicorn valuation!)
• See our data in action at The Anchor
• Placer.ai in the news
• Video: About Placer for Commercial Real Estate
• Video Playlist: Placer Brand & Explainer Videos

Placer.ai is committed to maintaining a drug-free workplace and promoting a safe, healthy working environment for all employees.

Placer.ai is an equal opportunity employer and has a global remote workforce. Placer.ai’s applicants are considered solely based on their qualifications, without regard to an applicant’s disability or need for accommodation. Any Placer.ai applicant who requires reasonable accommodations during the application process should contact Placer.ai’s Human Resources Department to make the need for an accommodation known.

Staff Data Platform Engineer

We are looking for a Staff Data Platform Engineer to join our Engineering team and lead the evolution of our next-generation data platform. In this high-impact role, you will operate as a player-coach: you will be the technical visionary responsible for designing the ecosystem, while remaining deeply hands-on to implement scalable, secure, and intelligent solutions that power everything from operational reporting to advanced GenAI applications.

You will bridge the gap between complex business requirements and technical execution, advocating for a data-first culture. This role offers a clear growth path: while it currently starts as an individual contributor position, it has the potential to evolve into a leadership role.

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.

About the Role

• Architecture & Hands-on Execution: Design and actively build a comprehensive data platform. You will not just oversee infrastructure; you will write the core code and build tools that support diverse workloads—from operational reporting to complex analytical queries.
• Strategic & Technical Delivery: Partner with product managers to translate business objectives into technical strategies, then lead the engineering effort to deliver them.
• Technology Evaluation: Continuously evaluate, prototype, and select best-in-class technologies to future-proof our data stack.
• Technical Leadership & Mentorship: Act as a primary advocate for platform adoption. You will foster a community of practice around data engineering, mentoring senior and mid-level engineers to elevate the team's technical bar.
• Governance & Quality: Implement and automate robust frameworks for Data Discovery, Quality, and Governance, ensuring solutions are trustworthy and compliant with financial regulations.

About you

We are looking for a highly motivated Staff Data Platform Engineer with a strong sense of ownership, eager to tackle technical challenges in a high-throughput data processing environment.

• Experience: 8+ years of hands-on experience in Data Engineering and Architecture, with a track record of building and shipping platforms at scale.
• Experience with modern big data platforms such as Snowflake, Databricks, or similar technologies.
• Hands-on experience with Data infrastructure experience (Orchestration, scalability, reliability, and cloud architecture).
• Data Movement & Integration: Deep understanding of data movement strategies, including high-frequency batching, CDC, and real-time event streaming.
• Technical Depth: Deep understanding of database internals. High proficiency in Python and SQL. You can dive into code when necessary to solve complex issues.
• Modeling & Architecture: Strong know-how in dimensional modeling and schema design (relational and NoSQL), with proven experience implementing Data Warehouse or Lakehouse architectures.
• GenAI & RAG Expertise: You have practical experience architecting and building RAG (Retrieval-Augmented Generation) pipelines, with specific knowledge of Vector Databases, Embedding Models, and LLM Orchestration frameworks.
• Business Acumen: A strong ability to understand business objectives and translate them into technical strategies that drive tangible value.
• Leadership and Communication: As this is a central role in the product tech organisation, you will need a strong ability to influence engineering teams and drive consensus without direct authority. You must have excellent communication skills to explain complex architectural concepts to C-level stakeholders and non-technical partners.

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.

Manager, Field Engineering Israel

Location: Herzliya

As a Field Engineering Manager, you will lead a team of technical pre-sales Solutions Architects and Solutions Engineers in Israel. Your experience partnering with the sales organisation will help drive revenue with the right approach whilst coaching sales and pre-sales teams to work together. 

You will guide and get involved to enhance your team's effectiveness; be an expert at communicating complex, business value-focused solutions, support complex sales cycles, and build relationships with important partners in large corporations.

The impact you will have:

• Hire, mentor and grow the pre-sales team in Israel
• Build a motivated collaborative culture within a hyper-growth team to embody and promote Databricks customer-obsessed, teamwork and diverse culture
• Support increased return on investment of SA involvement in sales cycles
• Ensure a solution and value-based selling within the field-engineering organization
• Display an understanding of needs and revenue potential for accounts in the assigned region
• Engage with key customer executives to build and strengthen strategic partnerships
• Ensure close alignment with partners and internal services to secure implementation strategies within accounts
• Continue to build Databricks' brand as a member of the Leadership team in partnership with Marketing and Sales teams across the region

What we look for:

• Experience managing a team of successful Big Data, Cloud, or SaaS professionals
• Experience in consumption based business environments
• Have experience mentoring and scaling technical teams
• Success in instituting processes for technical field members to lead efficiency and product focus
• Ability to partner and collaborate with Sales and other cross-functional leaders
• Passionate about data and AI market and Cloud software models and being able to deliver a strong POV on the value of Databricks solutions
• Technical or consulting background either in Data Engineering, Database technologies or Data Science
• Strong communication skills. Hebrew native-speaker and fluent in English.

About the role:

Forter is looking for a Senior Big Data Engineer to join our growing ML Platform team. This is a great opportunity for an experienced Data Engineer who wants to apply their skills to the world of Machine Learning. Together, we’ll provide the high-throughput tools and distributed systems needed to process billions of data points, ensuring that our models have the feature-rich, reliable data they need to perform in real-time.

ML is central to Forter’s work. It enables us to process billions of dollars worth of e-commerce transactions and identify fraud rings. Precision at scale is crucial—our models depend on engineered features derived from massive datasets. As the volume of data and the complexity of these models grow, we need senior engineers who can solve the "Big Data" challenges inherent in modern MLOps.

Why should you join us?

You’ll be part of a highly proficient engineering team that is the focal point for all ML engineering activity. This role is perfect for a Big Data specialist who wants to own the data-intensive side of ML—building the pipelines and infrastructure that transform raw global traffic into actionable intelligence.

What you will be doing:

• Designing and building the data-heavy components of our ML infrastructure, allowing Forter’s models to make billions of real-time decisions every year.
• Building distributed data processing pipelines that power model training, feature engineering, and offline research at scale.
• Optimizing the "Feature Store" concept—ensuring that the data used for training matches the data used in production for real-time serving.
• Acting as a technical consultant to data scientists and researchers, helping them navigate massive datasets and providing the Spark-based tooling they need to iterate faster.
• Expanding our ML data infrastructure to be scalable and efficient, focusing on the performance of data ingestion and transformation for diverse model types.
• Improving MLOps standards by ensuring data reproducibility, lineage, and quality across the entire model lifecycle.

Who are you?

• 5+ years of experience with large-scale data processing, with deep expertise in Apache Spark.
• 5+ years developing complex software with at least one general-purpose language (preferably Python or Scala).
• Backend and server-side development experience of complex, highly scalable systems.
• Strong understanding of Data Engineering patterns (Partitioning, Sharding, Schema evolution) and how they apply to model performance.
• Interest in Machine Learning concepts—you don't need to be a researcher, but you should understand how data flows into a model.
• Experience working with public clouds (AWS / GCP / Azure).
• Fluent in written and spoken English.

It’d be really cool if you also:

• Are familiar with Databricks or Airflow for orchestrating complex ML workflows.
• Are comfortable in a containerized environment (Kubernetes/Docker).
• Have experience with low-latency, real-time data serving or streaming (Kafka).

About the role: 

Forter is looking for a Senior Engineer with a data engineering background to join our growing ML Platform team. This is a great opportunity, whether you have experience with ML and are looking for a ML focused product or are an experienced Data Engineer looking to enter the world of ML. Together we’ll provide tools to develop more effective models, get them into production faster, and ensure that they continue to perform well over time.

ML is central to Forter’s work. It enables us to process billions of $ worth e-commerce transactions, make decisions in real time, identify fraud rings, and quickly detect new attack methods. Precision is crucial - bad decisions by our models cost us directly and put money into the pockets of fraudsters.

Our adoption by merchants around the world provides us with billions of fresh data points each day. Our team of data scientists, analysts, and cyber intelligence specialists continually identify new signals, engineer new features, and research new models. But as the volume of data and the number and complexity of models grows, so do the engineering challenges. 

If this kind of working environment sounds exciting to you, if you understand that Engineering is about building the most effective and elegant solution within a given set of constraints - consider applying for this position.

Why should you join us?

You’ll be part of a highly proficient engineering team that is a focal point for all ML engineering activity, striving to constantly bring innovation and leverage ML capabilities across all company teams and products.

This role presents a unique opportunity to enter the ML domain. For those already experienced in ML infrastructure, it offers the chance to grow within a team that specializes in high-scale, Big Data and ML systems.

What you will be doing:

• Designing, building, and maintaining the ML infrastructure that allows Forter’s models to make billions of real-time decisions every year. 
• Building a platform that enables managing a full ML model lifecycle - from researching to training, deploying, and serving predictions in real-time. 
• Building distributed data processing pipelines to support model development.
• Acting as a consultant to researchers, data scientists, and expert analysts and enabling them to research new models faster and with greater precision by providing cutting-edge tooling.
• Expanding our ML infrastructure to make it scalable, quick, and efficient to bring diverse models to production and to monitor their performance and drift over time.
• Expanding the pool of internal customers able to use ML at Forter. Work with them to understand their needs and help them make the most of the infrastructure that we’ll provide.
• Acting as an advocate for MLOps, continually improving our processes, and raising our standards.

Who are you?

• 4+ years experience with large-scale data processing, ideally with Apache Spark.
• 5+ years developing complex software projects with at least one of general-purpose languages (preferably Python, but not a must)
• Backend and server-side development experience of complex, highly scalable systems
• Experienced with machine learning concepts and frameworks.
• Motivation to understand the needs of internal users, provide them with great tooling, and teach them how to use it. 
• Experience working with public clouds (AWS / GCP / Azure)
• Fluent in written and spoken English

It’d be really cool if you also:

• Are familiar with Databricks or Airflow.
• Are comfortable in a containerized environment.
• Have experience with maintaining highly available, low latency, real-time services 

About us:

Digital commerce is built on trust. At every point along the eCommerce journey, businesses must make a critical decision: Can I trust this customer? Answering this simple question accurately and instantly is powerful—it can accelerate revenue growth and strengthen a company’s connection with its customers. How do we do it? Forter was founded on the insight that it's not about what is being purchased, nor where— but who is behind the interaction.

The Forter Decision Engine finds patterns across more than one billion identities in our dataset. We isolate fraudsters and protect customers—ensuring everyone gets the experience they deserve.  Given that trust is central to how we operate, Forter is very much driven by a defined set of values. We attract remarkable talent and have retention and engagement levels that are well above benchmarks. We’re meticulous about strengthening our culture as we grow and ensuring this is an environment where people can have outsized impact. 

Trust is backed by data –  Forter is a recipient of over 10 workplace and innovation awards, including: 

• Great Place to Work Certification (2021, 2022, 2023, 2024, 2025)
• Fortune’s Best Workplaces in NYC (2022, 2023, 2024 and 2025)
• Forbes Cloud 100 (2021, 2022, 2023, 2024 and 2025)
• #3 on Fast Company’s list of “Most Innovative Finance Companies” (2022)
• Anti-Fraud Solution of the Year at the Payments Awards (2024)
• SAP Pinnacle Awards “New Partner Application Award” (2023)
• Fintech Breakthrough Awards – Best Fraud Prevention Platform (2023)

Life as a Forterian:

We are a team of over 600 Forterians spread across 3 different continents. Since 2013, we've raised $525 million from investors such as Tiger Global, Bessemer, Sequoia Capital, March Capital and Salesforce Ventures. We're on a mission to bring trust to global digital commerce so that companies like Adobe, ASOS, eBay, Instacart, Priceline and Nordstrom can block fraud, drive revenue and improve customer experience.

At Forter, we believe unique people create unique ideas, and valuable experience comes in many forms. So, even if your background doesn't match everything we have listed in the job description, we still encourage you to apply and tell us why your skills and values could be an asset to us. By welcoming different perspectives, we grow together as humans and as a company.

Forter is an Equal Employment Opportunity employer that will consider all qualified applicants, regardless of race, color, religion, gender, sexual orientation, marital status, gender identity or expression, national origin, genetics, age, disability status, protected veteran status, or any other characteristic protected by applicable law.

If you need assistance or an accommodation due to a disability, please email us at interviewaccommodation@forter.com. This information will be treated as confidential and used only for the purpose of determining an appropriate accommodation for the interview process.

Axonius is seeking a Senior Software Engineer (Data Engineering). You will be responsible for designing and building all data, ML pipelines, data tools, and cloud infrastructure required to transform massive, fragmented data into a format that supports processes and standards. Your work directly empowers business stakeholders to gain comprehensive visibility, automate key processes, and drive strategic impact across the company.

Responsibilities

• Design and Build Data Infrastructure: Design, plan, and build all aspects of the platform's data, ML pipelines, and supporting infrastructure.
• Optimize Cloud Data Lake: Build and optimize an AWS-based Data Lake using cloud architecture best practices for partitioning, metadata management, and security to support enterprise-scale operations.
• Lead Project Delivery: Lead end-to-end data projects from initial infrastructure design through to production monitoring and optimization.
• Solve Integration Challenges: Implement optimal ETL/ELT patterns and query techniques to solve challenging data integration problems sourced from structured and unstructured data.

Minimum Qualifications

• Experience: 5+ years of hands-on experience designing and maintaining big data pipelines in on-premises or hybrid cloud SaaS environments.
• Programming & Databases: Proficiency in one or more programming languages (Python, Scala, Java, or Go) and expertise in both SQL and NoSQL databases.
• Engineering Practice: Proven experience with software engineering best practices, including testing, code reviews, design documentation, and CI/CD.
• AWS Experience: Experience developing data pipelines and maintaining data lakes, specifically on AWS.
• Streaming & Orchestration: Familiarity with Kafka and workflow orchestration tools like Airflow.

Preferred Qualifications

• Containerization & DevOps: Familiarity with Docker, Kubernetes (K8S), and Terraform.
• Modern Data Stack: Familiarity with the following tools is an advantage: Kafka, Databricks, Airflow, Snowflake, MongoDB, Open Table Format (Iceberg/ Delta)
• ML/AI Infrastructure: Experience building and designing ML/AI-driven production infrastructures and pipelines.

#LI-HYBRID #LI-ZR1 

Axonius is seeking a Senior Data Infra Engineer. You will be responsible for designing and building all data, ML pipelines, data tools, and cloud infrastructure required to transform massive, fragmented data into a format that supports processes and standards. Your work directly empowers business stakeholders to gain comprehensive visibility, automate key processes, and drive strategic impact across the company.

Responsibilities

• Design and Build Data Infrastructure: Design, plan, and build all aspects of the platform's data, ML pipelines, and supporting infrastructure.
• Optimize Cloud Data Lake: Build and optimize an AWS-based Data Lake using cloud architecture best practices for partitioning, metadata management, and security to support enterprise-scale operations.
• Lead Project Delivery: Lead end-to-end data projects from initial infrastructure design through to production monitoring and optimization.
• Solve Integration Challenges: Implement optimal ETL/ELT patterns and query techniques to solve challenging data integration problems sourced from structured and unstructured data.

Minimum Qualifications

• Experience: 5+ years of hands-on experience designing and maintaining big data pipelines in on-premises or hybrid cloud SaaS environments.
• Programming & Databases: Proficiency in one or more programming languages (Python, Scala, Java, or Go) and expertise in both SQL and NoSQL databases.
• Engineering Practice: Proven experience with software engineering best practices, including testing, code reviews, design documentation, and CI/CD.
• AWS Experience: Experience developing data pipelines and maintaining data lakes, specifically on AWS.
• Streaming & Orchestration: Familiarity with Kafka and workflow orchestration tools like Airflow.

Preferred Qualifications

• Containerization & DevOps: Familiarity with Docker, Kubernetes (K8S), and Terraform.
• Modern Data Stack: Familiarity with the following tools is an advantage: Kafka, Databricks, Airflow, Snowflake, MongoDB, Open Table Format (Iceberg/ Delta)
• ML/AI Infrastructure: Experience building and designing ML/AI-driven production infrastructures and pipelines.

#LI-HYBRID #LI-ZR1