We are looking for a Senior Data Engineer to take ownership of our evolving data platform.

Our data environment is entering a significant growth phase. We are strengthening our Redshift-based warehouse, expanding our transformation capabilities with dbt, and investing in modern engineering standards across the stack.

In parallel, we are building a dedicated application layer for delivering data products. This role is responsible for designing and owning the data foundations that support it.

AI-assisted development is not a side experiment. It is a core part of how we engineer. We expect this role to actively leverage advanced AI development tools as part of daily work, accelerating design, implementation, validation and documentation while maintaining strong architectural judgment and production-level quality.

This position requires architectural thinking, long-term platform vision and the ability to lead complex initiatives from design through production in an AI-augmented engineering environment.

What You Will Do:

Own the architecture and evolution of our cloud-based Data Warehouse.

Lead complex data initiatives end to end, from requirements definition and technical design through implementation, deployment and post-production optimization.

Apply AI-assisted development workflows to improve engineering velocity, code quality and system reliability.

Design and evolve transformation standards and modeling practices using dbt as a strategic layer within the team.

Architect the data foundations that power our data-driven applications.

Translate business needs into structured, production-grade data solutions.

Drive technical standards, consistency and engineering discipline across the data stack.

Take full accountability for delivery, stability and long-term scalability of the systems you build.

This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from our office.

We are looking for a highly skilled Senior Data Engineer with strong architectural expertise to design and evolve our next-generation data platform. You will define the technical vision, build scalable and reliable data systems, and guide the long-term architecture that powers analytics, operational decision-making, and data-driven products across the organization.

This role is both strategic and hands-on. You will evaluate modern data technologies, define engineering best practices, and lead the implementation of robust, high-performance data solutions-including the design, build, and lifecycle management of data pipelines that support batch, streaming, and near-real-time workloads.

What Youll Do

Architecture & Strategy

Own the architecture of our data platform, ensuring scalability, performance, reliability, and security.
Define standards and best practices for data modeling, transformation, orchestration, governance, and lifecycle management.
Evaluate and integrate modern data technologies and frameworks that align with our long-term platform strategy.
Collaborate with engineering and product leadership to shape the technical roadmap.

Engineering & Delivery

Design, build, and manage scalable, resilient data pipelines for batch, streaming, and event-driven workloads.
Develop clean, high-quality data models and schemas to support analytics, BI, operational systems, and ML workflows.
Implement data quality, lineage, observability, and automated testing frameworks.
Build ingestion patterns for APIs, event streams, files, and third-party data sources.
Optimize compute, storage, and transformation layers for performance and cost efficiency.

Leadership & Collaboration

Serve as a senior technical leader and mentor within the data engineering team.
Lead architecture reviews, design discussions, and cross-team engineering initiatives.
Work closely with analysts, data scientists, software engineers, and product owners to define and deliver data solutions.
Communicate architectural decisions and trade-offs to technical and non-technical stakeholders.

We're looking for a Data Warehouse Tech Lead to drive the technical vision and execution of our data infrastructure that powers decision-making across.
You'll lead both the technology and the business coordination for our data warehouse - architecting scalable solutions while working closely with stakeholders and data providers to ensure our platform serves the entire organization's needs. This role combines deep technical leadership with strategic business partnership as we build our next-generation data stack.
We believe three things matter for every role: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll:
Lead technical architecture - design and develop scalable data warehouse solutions that support multiple products and serve the entire organization's analytics needs
Manage the technical roadmap - set strategy and guide execution for the Data Warehouse team, ensuring our platform evolves with business requirements
Drive business process coordination - translate business needs into technical requirements while establishing clear data contracts with R&D, Analytics, and external data providers
Establish and implement best practices - set technical standards for data warehouse architecture, performance tuning, and development methodologies that guide the entire team's approach to building scalable data solutions
Create and maintain sustainable data pipelines - build resilient systems capable of handling unstructured data and managing an evolving schema registry across diverse data sources
Implement advanced data modeling - create robust data structures using methodologies like dimensional modeling, and optimize ETL/ELT processes for our semantic layer
Establish data quality standards - build processes for schema evaluation, anomaly detection, and monitoring data completeness and freshness across all sources
Lead cross-team collaboration - work directly with Data Engineers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers to align technical solutions with business goals

Were looking for an experienced Data Engineer to join our DataWarehouse team in TLV.
In this role, you will play a pivotal role in the Data Platform organization, leading the design, development, and maintenance of our data warehouse. In your day-to-day, youll work on data models and Backend BI solutions that empower stakeholders across the company and contribute to informed decision-making processes all while leveraging your extensive experience in business intelligence.
This is an excellent opportunity to be part of establishing our state-of-the-art data stack, implementing cutting-edge technologies in a cloud environment.
We believe three things matter for every role: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role youll:
Lead the design and development of scalable and efficient data warehouse and BI solutions that align with organizational goals and requirements
Utilize advanced data modeling techniques to create robust data structures supporting reporting and analytics needs
Implement ETL/ELT processes to assist in the extraction, transformation, and loading of data from various sources into the semantic layer
Develop processes to enforce schema evaluation, cover anomaly detection, and monitor data completeness and freshness
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency
Implement best practices for data warehouse and database performance tuning
Conduct thorough testing of data applications and implement robust validation processes
Collaborate with Data Infra Engineers, Developers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers

we are looking for a Senior Data Engineer responsible for designing, building, and maintaining the infrastructure necessary for analyzing large data sets. This individual should be an expert in data management, ETL (extract, transform, load) processes, and data warehousing and should have experience working with various big data technologies, such as Hadoop, Spark, and NoSQL databases. In addition to technical skills, a Senior Data Engineer should have strong communication and collaboration abilities, as they will be working closely with other members of the data and analytics team, as well as other stakeholders, to identify and prioritize data engineering projects and to ensure that the data infrastructure is aligned with the overall business goals and objectives.
What You'll Do
Work closely with data scientists/analytics and other stakeholders to identify and prioritize data engineering projects and to ensure that the data infrastructure is aligned with business goals and objectives
Design, build and maintain optimal data pipeline architecture for extraction, transformation, and loading of data from a wide variety of data sources, including external APIs, data streams, and data stores.
Continuously monitor and optimize the performance and reliability of the data infrastructure, and identify and implement solutions to improve scalability, efficiency, and security
Stay up-to-date with the latest trends and developments in the field of data engineering, and leverage this knowledge to identify opportunities for improvement and innovation within the organization
Solve challenging problems in a fast-paced and evolving environment while maintaining uncompromising quality.
Implement data privacy and security requirements to ensure solutions comply with security standards and frameworks.
Enhance the team's dev-ops capabilities.

We are looking for a Staff Software Data 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 us?

we are 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. our 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 our company, we pride ourselves on our collaborative culture, the quality of our product and the capabilities of our people. we are passionate about the work they do, and keen to get the job done. we offer 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, our company 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.

We are looking for a talented Data Engineer to join our analytics team in the Big Data Platform group.
Job Id: 25380
You will support our product and business data initiatives, expand our data warehouse, and optimize our data pipeline architecture with an AI first attitude.
The ideal candidate is experienced in leveraging AI tools as part of modern data pipeline development, enabling scalable solutions, accelerating delivery, and continuously exploring new approaches and technologies.
The right candidate is excited by the prospect of building the data architecture for the next generation of products and data initiatives.
This is a unique opportunity to join a team full of outstanding people making a big impact on us.
We work on multiple products in many domains to deliver truly innovative solutions in the Cyber Security and Big Data realm.
This role requires the ability to collaborate closely with both R&D teams and business stakeholders, to understand their needs and translate them into robust and scalable data solutions.
Key Responsibilities
Maintain and develop enterprise-grade Data Warehouse and Data Lake environments
Create data infrastructure for various R&D groups across the organization to support product development and optimization
Work with data experts to assist with technical data-related issues and support infrastructure needs
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, redesigning infrastructure for scalability
Build and maintain robust ETL/ELT pipelines for data ingestion, transformation, and delivery across various systems
Incorporate AI-assisted tools into data pipeline design, development, and optimization to improve efficiency, scalability, and innovation

We are building a centralized intelligence system for the entire organization - a system that collects, consolidates, and analyzes all organizational data, and actively drives business workflows and decision-making.
This role exists to take that system to the next level.
As the Lead Organizational Intelligence Engineer, you will own the evolution of an internal platform that already influences how decisions are made across the company - and turn it into a foundational capability that fundamentally reshapes how the organization operates. Youll work end-to-end: from data ingestion and modeling, through analytics and AI-driven insights, all the way to decision workflows used by executives, R&D, product, and go-to-market teams.
You will operate as a senior individual contributor with broad organizational influence, while laying the technical and product foundations for a future team.
What Youll Do:
Own the architecture and implementation of a company-wide organizational intelligence system, end-to-end
Design and build data pipelines that ingest and unify data from across the organization and into our own platform
Define and evolve data models and semantic layers that create a shared, consistent language across teams and domains
Build advanced analytics and insight mechanisms that move beyond dashboards into decision-enabling workflows
Work directly with company executives to co-define requirements, identify blind spots, and translate strategic questions into systems and capabilities
Apply a product-driven mindset: deciding not just how to build, but increasingly what should be built and why
Leverage frontier AI tooling and agent-based workflows to accelerate development, improve system quality, and expand whats possible
Write and own production-grade code, setting a high bar for quality, reliability, and scalability
Influence technical and organizational workflows across the company to enable deeper intelligence and better decisions
Lay the groundwork for future externalization of these capabilities into customer-facing products

Required Data Engineer, Product Analytics
As a Data Engineer, you will shape the future of people-facing and business-facing products we build across our entire family of applications. Your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide.
In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across to optimize growth, strategy, and user experience for our 3 billion plus users, as well as our internal employee community.
You will be at the forefront of identifying and solving some of the most interesting data challenges at a scale few companies can match. By joining us, you will become part of a world-class data engineering community dedicated to skill development and career growth in data engineering and beyond.
Data Engineering: You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions. You will refine our systems, design logging solutions, and create scalable data models. Ensuring data security and quality, and with a focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems.
Product leadership: You will use data to shape product development, identify new opportunities, and tackle upcoming challenges. You'll ensure our products add value for users and businesses, by prioritizing projects, and driving innovative solutions to respond to challenges or opportunities.
Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Engineer, Product Analytics Responsibilities
Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights visually in a meaningful way
Define and manage Service Level Agreements for all data sets in allocated areas of ownership
Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Solve our most challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts
Influence product and cross-functional teams to identify data opportunities to drive impact
Mentor team members by giving/receiving actionable feedback.