דרושים » הנדסה » Software Engineer, Lakehouse (Data Platform Group)

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.

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 on a mission to create public transportation systems that provide far greater access to jobs, healthcare, and education. Our platform serves as the technology backbone for modern transit networks, transforming antiquated and siloed public transportation systems into smart, data-driven, and efficient digital networks. With hundreds of agency partners around the world, we are recognized as the leading transportation technology and service provider globally.
As a Software & Data Engineer at our company, you will play a central role in building and evolving the data infrastructure that powers one of the world's leading transportation platforms. You'll work with rich, complex transportation data - from ride bookings and payments to real-time operational signals - designing the pipelines and systems that turn raw data into clean, reliable, and actionable insight across the business. This is a high-ownership role on a talented and deeply motivated engineering team in Tel Aviv, where your work will directly shape how our company understands and improves its service for cities and riders around the world.
About the Role:
Design and build highly scalable, reliable data pipelines that serve clean, structured data across our company's engineering, product, and business teams - ensuring the entire organisation can trust the data it works with
Own the architecture of complex data models that translate messy, real-world transportation data - bookings, payments, driver activity, and more - into systems that are fast, efficient, and built to scale
Lead end-to-end development across the full data lifecycle: from architecture and design through to deployment, monitoring, and continuous improvement
Proactively monitor data quality and reliability, identifying and resolving discrepancies before they reach stakeholders - building the kind of data infrastructure people can depend on
Collaborate with a broad forum of engineers, analysts, and business stakeholders to identify data needs, design POCs, and ship scalable solutions that make a real difference to how our company operates
Contribute to the adoption and evolution of our modern data stack, including DBT, Airflow, Iceberg storage, and AWS big data tooling such as Glue, EMR, and Athena.

We are seeking a highly skilled and versatile Performance Research and Analysis Manager to join our Performance Group. This role will drive end-to-end performance strategy and execution for our next-generation data centers and solutions based on GPU systems, NIC, Switch, DPU and Networking technologies. The ideal candidate will oversee, evaluating, and optimizing end-to-end AI GPU cluster-level performance for scaling out large scale distributed training and inference jobs communication. The role will focus heavily on RDMA, Networking Protocols, Collective Communication, Congestion Control, and Load Balancing algorithms. Secondarily, you will lead our DPUs and Storage technologies for N-S use cases to support AI Inference jobs. Third, you will drive our Performance Dashboards and Observability for cluster-level performance analysis from a stream line telemetry across NICs, Switches, GPUs, and NVlink.

What you'll be doing:

Drive end-to-end performance strategy, characterization, test plans, and optimization for our next-generation AI GPU clusters, focusing on large-scale distributed training and inference workloads.

Deeply evaluate and optimize our Networking core technologies performance, including RDMA/PRDMA, networking protocols, collective communication (NCCL), congestion control, and load-balancing algorithms.

Work on performance research and analysis of our DPUs and storage technologies in North-South (N-S) use cases and deployment scenarios to maximize performance and efficiency for AI inference jobs.

Drive the strategy for performance observability and dashboards across our next-generation data center solutions and supercomputers by leveraging scalable, streamlined telemetry pipelines to build performance dashboards and automated analytics based on real-time performance metrics across NICs, Switches, GPUs, and NVLink boundaries.

Perform deep root-cause analysis (RCA) on complex multi-node performance bottlenecks, driving actionable mitigation plans across hardware, firmware, and software teams.

The Senior Backend Engineer team (Data Team) builds the systems that discover, understand, and govern customer data at petabyte scale. We turn raw enterprise data into the security signal the rest of the platform builds on, working on problems like distributed systems running inside customer clouds, analytics over large data lakes, and detection logic that has to be both precise and fast. Youll work end-to-end and ship features that every Sentra customer uses.

Responsibilities
Designing and implementing core components within the classification and policy stack, including microservices, ETLs, and shared libraries.
Owning features end-to-end: design, implementation, rollout, testing, monitoring, and production operation.
Conducting design and code reviews with the team and across R&D.
Driving scale, performance, and cost optimizations against multi-tenant data-lake workloads.
Partnering with AI/ML, Research, Product, and Frontend to ship cross-functional initiatives.

We are at the forefront of the AI revolution, delivering brand new accelerated compute platforms for global impact. Our Network Architecture group is seeking a talented and motivated Sr. Software Engineer to build the agentic workflows that our architects use in their daily work. The software at the center of this role is our hardware network simulation environment - you will design multi-step agent workflows over it, engineer the context that grounds them in our own specifications and source code, and optimize their runtime performance. If you are passionate about building the practical infrastructure that brings intelligent agents to life, we want to hear from you.


What you'll be doing:
Build agentic workflows - loops, graphs, and multi-step pipelines - that carry real hardware network simulation and analysis work end to end.
Engineer the context these workflows run on, turning our simulation models, specifications, design documents, and source code into context that makes agents accurate in our domain.
Work closely with network architects to understand their workflows and translate them into agent workflows they use daily.
Optimize the runtime performance of our simulation tooling on these platforms, including execution time, compute cost, and end-to-end latency.
Define evaluation and regression testing for agent workflows, so that changes to a prompt, a graph, or a context source are measurable.
Build observability across agent runs: what the agent did, where it failed, and why.
Champion guidelines for secure and reliable agent workflows, including data handling, access control, and interaction boundaries.
Serve as a key technical resource for solving sophisticated integration issues between agents and internal tooling.

The Networking Diagnostics team is seeking a highly motivated and experienced engineer. This person must have hands-on technical expertise to develop critical diagnostic tools for our newest, world-leading networking platforms. This position offers the opportunity to have a real impact in a dynamic, technology-focused company, impacting data centers and high-performance computing (HPC) clusters across the world. We are looking for independent engineers who excel in a fast-paced environment and are passionate about ensuring the stability of next-generation hardware.

What you'll be doing:
Design & Implement: Architect and develop high-performance diagnostic tools and frameworks using Python, tailored for our latest networking platforms.
Performance Optimization: Drive end-to-end development focusing on software that performs efficiently, ensuring diagnostic suites can handle high-throughput data and real-time monitoring without latency.
System Diagnostics: Take charge of developing features that bridge the gap between complex hardware behaviors and software-level diagnostics.
Collaborative Problem Solving: Partner with hardware, firmware, and driver teams to address real-world challenges that demand innovative solutions and a customer-centric approach.
Autonomous Execution: Own the full software development lifecycle of diagnostic features, from initial hardware specification to deployment in dynamic environments.

We are looking for a Data Products Engineer to take full ownership of our internal product suite - the full-stack applications, AI agent tools, and automation pipelines that power teams across the entire company every day. You will step into an established ecosystem and take the reins. Your mission is to maintain, evolve, and build the next generation of these internal tools so every department can move faster and make smarter, data-driven decisions.

Reporting directly to the VP of CS & Data, this is a high-autonomy, tech-lead role. You wont just write code; you will make architectural decisions, solve complex domain challenges with smart software, and shape how the entire company interacts with data.

How will your day-to-day look?
Own the Internal Product Suite: Lead the development of our core full-stack applications. You will build and scale the central platforms and dashboards that give Product, CS, Sales, and executive leadership visibility into product usage, account health, business performance and more.
Advance the Internal AI Layer: Design, deploy, and refine custom agentic AI workflows - enabling teams across the organization to query complex B2B and product data naturally and conversationally.
Engineer Smart Automations: Architect workflow automations and custom APIs that pipe downstream data directly into the operational tools our teams use every day.
Bridge Data and Software: Partner seamlessly with Data Ops and Data Analysts to transform raw data models into highly usable, intuitive user interfaces and automated actions.
Run the Infrastructure: Own the end-to-end DevOps lifecycle for our internal applications, managing deployment, containerization, observability, and CI/CD pipelines.
Drive Technical Strategy: Act as the technical anchor for internal tools. You will translate high-level product and business challenges from company leaders into shipped, reliable software.

Were looking for a Hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities-from LLMs and agents to product data insights-are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making.

Key responsibilities

Lead a team of data scientists, data engineers and product analysts.

Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation.

Drive excellence, code quality, and best development practices.

Provide technical direction and hands-on guidance for complex AI systems.

Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences.

Ensure AI solutions are safe, scalable, observable, and continuously improving.

Lead initiatives around product data analysis and experimentation.

Analyze user interactions with product features to improve accuracy, UX, and business impact.

Partner with product teams to define metrics, dashboards, and experiments that guide product improvements.

Design system architectures for AI-enabled applications at scale.

Evaluate and select technologies for AI platforms and data pipelines.

Guide the development of prompt engineering frameworks and centralized prompt management.

Ensure robust monitoring, evaluation, and feedback loops for AI outputs.

Translate product and business goals into technical roadmaps and execution plans.

Drive alignment between AI capabilities and measurable product outcomes.

We are looking for a talented Senior Software infrastructure and tools Engineer to join the Data Processing Unit (DPU) SW Group. As a part of the team, you will lead complicated integrations which combining new technologies, automating processes, bringing up full software stacks, developing system scripts for cutting edge networking technologies with the quality requirements of industry-leading customers. You will work closely with our SDK development and gain an understanding of our products and technologies.

What youll be doing:

Crafting efficiency and usability improvements across our proprietary products that will help streamline various release pipelines and processes across us.

Definition and development of SDKs to be used for DPU SW development.

POC of new technologies that require additional development/integration efforts.

Creating and maintaining build system for complex SW products.

Developing tools using our various proprietary and other cutting-edge technologies.

Collaborate with team members, Architects, design, QA teams, and verification.