דרושים » תוכנה » staff engineer - data platform

we're looking for a tech lead who is more than a great data engineer - someone who brings equal depth in backend software engineering and broad fluency across data technologies, databases, and large-scale distributed systems. you'll own the architecture and hands-on development of our data platform while driving engineering excellence across the team.
design, build, and maintain large-scale batch and streaming data pipelines ( ETL /elt) across multiple products
develop and optimize spark workloads for performance, cost, and reliability on large data volumes
build and evolve our data lake / lakehouse, including data modeling, partitioning, and Storage formats
write production-grade backend services and rest apis that expose data platform capabilities
build in data quality, observability, and monitoring from the start, and own your pipelines in production end to end
automate and improve the data platform, including ai-assisted development and llm-powered data workflows
work closely with r&d and product teams, and contribute to design and code reviews.

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

The Data-Nexus team, a central part of the R&D department at our company, is seeking a versatile Senior Data Engineer to take part in leading our companys data vision using a lake-house architecture, and building high-scale solutions for handling and consuming the different data assets of the company.
In this role youll go beyond traditional boundaries, taking on full product responsibilities - from conceptualization and architecture to design, maintenance, and continuous development. You will collaborate closely with stakeholders across the company to ensure our solutions effectively meet their needs.
The ideal candidate will have strong data engineering capabilities, along with software development skills including understanding of designing and managing AWS cloud infrastructure and strong knowledge of different data architectures, methods and tools.
Responsibilities
Design and development of scalable, reliable, and secure data infrastructure and build ETL pipelines that handle diverse clinical data for research. Write production SQL, Spark jobs and craft schemas that evolve gracefully as research and production questions change.
Automate releases with CI/CD and Infrastructure as Code.
Optimise throughput, latency and cloud cost to meet research timelines at large scale.
Develop and maintain high-quality, scalable, and efficient code while fostering a culture of continuous improvement through regular retrospectives and knowledge sharing.
Take ownership of the full development lifecycle, including requirement gathering, design, implementation, testing, deployment, and ongoing maintenance.
Collaborate with cross-functional teams, including data scientists, data analysts, product managers, regulatory teams, and other developers, to drive the development of new tools and features that support our company's mission.
Explore and adopt new technologies and frameworks that can enhance the capabilities of the Data-Nexus team and the overall data projects in our company.

Required Staff Engineer - Office of the CTO
As a member of the Office of the CTO, your mission is to make every engineer 10x more effective. You will be a central driver in reimagining our Software Development Lifecycle (SDLC), building the intelligent platforms, automated golden paths, and AI-powered tools that will fundamentally change how we build software. This is a rare opportunity to have a massive, force-multiplying impact on our entire R&D & Product organizations, building the systems that enable hundreds of engineers to innovate faster and deliver with exceptional quality. The role is based in our Tel Aviv office.
Key Responsibilities:
Shape the Software Factory: Act as a key thought leader in shaping our Software Factory - the agentic workflows and loops that carry work from idea to production. You will research, prototype, and build the agents, harnesses, and tools behind them, and define the governance, controls, and standards that keep the factory predictable and safe at scale.
Build the Platform Beneath It: The factory only runs on solid foundations, and the Office of the CTO owns them. You will take a hands-on role in building and scaling the shared infrastructure every agentic workflow depends on - our AI gateway, shared memory and context graphs, guardrails, and the golden paths that abstract this complexity away from the teams using it.
Make Quality Automatic: Turn those standards into enforcement - automated gates in our CI/CD pipelines, evaluations and guardrails for agent-generated work, and the telemetry that tells us whether the factory is actually producing better outcomes. Quality, testing, security, and reliability become the default, not the exception.
Drive Adoption & Foster Community: Champion the tools you build. You will create documentation, lead workshops, and act as an internal advocate for your users, turning their feedback into the next iteration. You will also mentor and guide builders across R&D and product - in Tel Aviv and across our global sites - helping to foster our AI-native culture.

We are looking for a Staff Engineer to join our Core Engineering group. The group is responsible for the real-time, low-latency infrastructure that powers our fraud decisions and external APIs.
Our systems process billions of requests every day, ensuring high availability, security, and performance at global scale.
In this role, youll work on core backend components such as our decision engine, ingestion and enrichment pipelines, schema management systems, and self-serve API platform. The software you build will power critical business decisions and directly serve some of the worlds largest merchants.
This is a high-impact, high-ownership position for an engineer who thrives on solving complex distributed systems challenges, cares deeply about production-grade quality, and wants to shape the foundation of our decisioning platform.
What you'll be doing:
Design, build, and scale backend systems that power our real-time decisioning and APIs.
Own projects end-to-end - from design and implementation to production rollout and monitoring.
Ensure systems are low-latency, fault-tolerant, and high-throughput across distributed environments.
Enhance observability, reliability, and developer experience through strong operational and tooling practices.
Collaborate with Product, analysts, data scientists, and infrastructure teams to drive innovation across our decision ecosystem.
Participate in technical discussions and customer interactions, providing expertise and clear communication when supporting enterprise integrations.

We are looking for a Backend Engineer with deep data engineering expertise to build and evolve the systems that power product, analytics, experimentation, and AI development.
You will work across production backend services and data infrastructure, taking technical ownership of the full data lifecycle - from event ingestion and real-time processing to orchestration, modeling, quality, and reliable data access. This role combines hands-on backend development with ownership of shared data platform, working closely with backend, frontend, AI, DevOps, analytics, and product teams.
What you'll do:
Build and maintain production-grade Python and Java backend services, APIs, and reactive data-processing pipelines with clear interfaces, resilient failure handling, and comprehensive observability.
Own and evolve batch and streaming data pipelines supporting product analytics, learner insights, experimentation, and AI model training.
Design and maintain trusted data models, shared metrics, and semantic-layer business logic across the analytical data platform.
Define and enforce standards for data contracts, testing, lineage, freshness, and observability.
Develop reliable approaches to schema evolution, backfills, replay, workload distribution, and failure recovery.
Collaborate with DevOps, backend, frontend, AI, analytics, and product teams to deliver reusable data capabilities and maintain clear system boundaries.

We are looking for a Senior Software Engineer to join our growing Data Infrastructure team!
The team's main responsibility is developing our data platform - from building the microservices and pipelines that onboard customer data into our platform, to the infrastructure and tooling that enables our internal data teams to analyze, transform, process, and collect data independently. Our goal is to build leverage: every feature we ship reduces friction for the teams that depend on our platform. We're looking for a builder who takes full ownership from inception to production, cares deeply about quality and performance, and leverages AI tools to move faster and deliver better outcomes.
Responsibilities
Design and implement scalable, production-grade data pipelines and microservices that ingest, transform, and move data from a wide variety of customer sources at high volume.
Build and maintain high-performance backend services and APIs that interface with our data ecosystem, ensuring reliability, low latency, and security.
Develop and evolve the platform infrastructure - data warehouse, orchestration, compute - that internal data teams rely on daily.
Identify opportunities to automate recurring workflows and turn ad-hoc needs into robust, self-serve platform capabilities.
Collaborate with data scientists, analysts, and engineers across R&D to translate requirements into platform features.
Drive code quality through design reviews, code reviews, and adherence to engineering best practices.
Leverage AI tools throughout the full engineering cycle - from scoping and design to implementation and debugging - to deliver faster, higher-quality outcomes.

Required Senior Software Engineer, Cloud Datastream and Database Migration Service
About the job
Our software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
The Control & Connect (C&C) team builds the core infrastructure powering our DMS and Datastream. We own the mission-critical Control Plane and Data Movement Infrastructure that allows enterprise customers to seamlessly migrate and replicate their databases at massive scale.
As a Senior Software Engineer, you will design and build the core infrastructure that enables enterprise customers to replicate and migrate their databases. You will address distributed systems issues involving stateful microservices, intricate multi-region architectures, and high-throughput data pipelines. Operating in a collaborative environment, you will guide the technical design of new features, improve system reliability, and mentor fellow engineers. Our team is also pioneering AI-assisted engineering operations, giving you the opportunity to shape how we use generative AI to accelerate development, improve testing, and reduce operational toil.
Responsibilities
Design and implement resilient, multi-step long-running operations and manage orchestration workflows on our cluster management systems.
Drive architectural improvements to decouple systems, manage service overload, and integrate seamlessly with various Cloud services like AlloyDB, Cloud SQL, and BigQuery.
Take end-to-end ownership of ambiguous technical challenges, translating complex requirements into concrete architectures and maintaining high engineering standards through design and code reviews.
Identify and eliminate operational toil, including contributing to the team's custom AI agents to automate release pipelines and streamline on-call workflows.

at the company, we're revolutionizing the way businesses interact with the digital world by revealing to them everything that happens online. our cutting-edge platform and unique data empower over 4,300 customers globally, including industry giants like google, ebay, and adidas, to make game-changing decisions that drive their digital strategies.
in 2021, we went public on the new york stock exchange, and we havent stopped growing since!
were looking for an infrastructure data engineer to join our data labs ( DL ) department, which specializes in Professional Services for our super-premium customers. this role will report to our DL (datalabs) infrastructure team manager in the r&d.
why is this role so important at the company?
we are a data -focused company, and our unique ai and Machine Learning capabilities are the center of our business.
as a data infrastructure engineer in the datalabs group, you will be the technical backbone supporting our data production, analyst, and data science teams. you will own and maintain our aws cloud accounts and databricks workspaces, optimize pipeline executions, and proactively modernize our tech stack to reduce tech debt - ensuring our platform remains scalable, reliable, fast, and cost-effective.
given the business-oriented nature of datalabs, you will work closely with cross-functional stakeholders and internal teams who interface directly with strategic customers. by unblocking operational bottlenecks and building robust tooling, you will empower our analysts and data scientists to deliver custom, high-value data products to our customers seamlessly.
so, what will you be doing all day?
environment & workspace management: administering and optimizing our groups aws cloud accounts, iam policies, and databricks workspaces to ensure peak performance, rock-solid security, and cost efficiency.
execution & pipeline infrastructure: owning the health, reliability, and scaling of our core data execution environments (airflow, docker, eks/ecs, distributed queues, and database engines).
tech debt modernization: proactively researching, benchmarking, and replacing legacy debt with modern technologies to keep our platform fast and cutting-edge.
Developer & production support: serving as the technical focal point for internal analysts and data science teams-providing the tooling, standards, and infra support they need to build custom client reports smoothly.
cross-group & client alignment: partnering with external engineering teams and internal stakeholders to support custom data delivery pipelines and uphold high-priority customer slas.
why youll love being a team member:
youll actually love the product you work with: our customers arent our only raving fans. when we asked our employees why they chose to come work at the company, 99% of them said the product.