דרושים » דאטה » Senior Data Engineer

As a Senior Big Data Engineer, working within Mobility Group, you will play a pivotal role in designing, developing, and maintaining the data infrastructure that powers our location analytics platform.
RESPONSIBILITIES:

Data Pipeline Architecture and Development: Design, build, and optimize robust and scalable data pipelines to process, transform, and integrate large volumes of data from various sources into our analytics platform.
Data Quality Assurance: Implement data validation, cleansing, and enrichment techniques to ensure high-quality and consistent data across the platform.
Performance Optimization: Identify performance bottlenecks and optimize data processing and storage mechanisms to enhance overall system performance and reduce latency.
Cloud Infrastructure: Work extensively with cloud-based technologies (GCP and AWS), to design and manage scalable data infrastructure.
Collaboration: Collaborate with cross-functional teams including Data Analysts, Data Scientists, Product Managers, and Software Engineers to understand requirements and deliver solutions that meet business needs.
Data Governance: Implement and enforce data governance practices, ensuring compliance with relevant regulations and best practices related to data privacy and security.
Monitoring and Maintenance: Monitor the health and performance of data pipelines, troubleshoot issues, and ensure high availability of data infrastructure.
Mentorship: Provide technical guidance and mentorship to junior data engineers, fostering a culture of learning and growth within the team.

We are looking for an experienced Data Infrastructure Team Lead to lead our Data Infrastructure team. In this role, you will have formal people-management responsibility for a multidisciplinary team that builds, productionizes, and improves big data and analytics infrastructure. You will be responsible for team delivery, combining technical depth, agile leadership, and an AI-first mindset to help the team build reliable systems, improve how it works, and continuously raise its engineering standards.

Location: Ramat Gan (Bursa area), Israel - Hybrid model

What will you do?

Lead, manage, and develop a data infrastructure team of approximately 5-7 people.
Take responsibility for team delivery, including planning, prioritization, execution, and continuous improvement.
Lead agile ways of working, including scrum-based delivery practices.
Guide the design, productionization, and ongoing improvement of big data and analytics infrastructure.
Partner closely with cross-functional stakeholders across technical, scientific, and business interfaces.
Help the team adopt AI-first engineering practices, including automation and AI-assisted development workflows.
Drive improvements in team processes, technical quality, delivery predictability, and collaboration.
Support architectural and technical decisions across cloud infrastructure, data pipelines, orchestration, and production systems.
Create an environment where team members can grow, contribute, and improve together.

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers our data, AI, and research platforms. This is a senior player-coach role with broad architectural ownership across data infrastructure, ML infrastructure, developer experience, reproducibility, and production reliability. You will work across the wider engineering group as a hands-on technical architect, while also managing a small team of individual contributors focused on ML infrastructure.

This role is ideal for someone who can move between long-term platform architecture and practical execution: defining standards, building core systems, mentoring engineers, improving reliability, and partnering with Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics, and Leadership to make our data and AI platforms scalable, reproducible, secure, compliant, and easier to use.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Architectural Leadership: Own and evolve the technical roadmap for our data and AI platforms, ensuring scalable and reliable architecture that supports current needs and prepares for a multi-cloud future.
MLOps & Platform Development: Design and build end-to-end MLOps systems-covering experimentation, training, reproducibility, and deployment-while managing specialized infrastructure like BigQuery, orchestration tools (Dagster/Airflow), and R/Python workloads.
Infrastructure Strategy: Define and lead strategy for GPU resources (scheduling, utilization, batch compute) and establish engineering best practices, data architecture standards, and platform guardrails.
Developer Experience: Enhance developer productivity by building self-service platforms, automation, internal tooling, and reusable templates that simplify workflows and reduce operational friction.
Team Leadership: Act as a player-coach to mentor engineers and manage a small team of ICs, fostering a culture of sound decision-making and technical excellence across the broader group.
Security & Reliability: Partner with Security to enforce compliance (SOC2, HIPAA, GDPR) and access controls, while mitigating operational risk through improved observability, incident readiness, and robust support processes.

As an Engineering Manager in the data department, youll build and scale our data platform and data apps that powers our business insights. Youll design and implement robust pipelines to process billions of daily records, leveraging cutting-edge cloud technologies to transform data into actionable intelligence.

If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!

Responsibilities
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
Architect and scale batch and streaming pipelines powering core business and ML use cases.
Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
Ensure reliability, scalability, and observability of large-scale data and ML systems in production.

We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).

We are hiring an Engineering Manager to own and grow the Data Science group - the R&D team behind our company's security and safety AI models and the data platform that powers them. You will lead a multidisciplinary team of ML engineers, data scientists, and software engineers who ship real-time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath. This is a hands-on people-leadership role: you set technical direction, are accountable for delivery and quality, and you build and grow the team.
What your team owns
The group is responsible for a large Python + Rust + PySpark monorepo (dozens of production services and shared libraries) spanning three connected domains:
1. Content-moderation inference at scale
Real-time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through an in-house ActiveServe framework over NVIDIA Triton and a Rust detection monolith, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models.
2. GenAI safety & red-teaming
Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok) and forming our company's leading edge into agentic-AI safety.
3. Data platform & MLOps
An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection.
What you'll do
Lead and grow the team - mentor ML engineers, data scientists, and software engineers, and own hiring, onboarding, 1:1s, career development, and performance.
Set direction and deliver - set technical direction and standards, turn company and product goals into a prioritized roadmap, and own the quality, reliability, and delivery of the systems above across parallel workstreams.
Champion excellence and partnership - stay hands-on to review designs and unblock the team, drive engineering excellence (testing, observability, CI/CD, on-call, cost/latency), keep the team at the state of the art in ML, LLMs, and GenAI safety, and partner with Product, Platform, and GenAI-safety stakeholders.
Leadership competencies
People-first: builds trust, grows engineers, and creates a healthy, inclusive, high-ownership culture.
Outcome-oriented: drives clarity, sets priorities, and delivers under ambiguity without micromanaging.
Technical credibility: earns the team's respect through sound judgment on architecture and trade-offs.
Systems thinker: balances short-term delivery against long-term platform health, cost, and tech debt.

Required Senior Software Engineer, Cloud Security
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.
Our engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information. As an engineer on this team, you will take autonomous ownership of critical infrastructure components that power Chronicle Security Orchestration, Automation and Response (SOAR). Our products are used by GCPs biggest and most important customers, requiring the highest level of Enterprise-grade reliability, performance, and security.
You will not simply implement others' ideas; you will be expected to scope complex operational challenges, recommend comprehensive software-driven solutions, and drive outcomes for your immediate area. You will work closely with cross-functional partners to translate functional and non-functional needs into robust, scalable, and secure architecture, transforming operational challenges into robust, software-driven solutions in close partnership with product development teams.
Responsibilities
Own all aspects of your immediate area, leading the design, building, and maintenance of software and systems that enhance the reliability, availability, and performance of Chronicle SOAR.
Set technical direction and priorities for software tools, platforms, and services that automate complex operational workflows, reduce manual toil, and improve the efficiency of managing Chronicle SOAR at scale.
Develop and manage infrastructure configurations and policies using Go to ensure secure, consistent, and auditable management of GCP resources.
Design and implement sophisticated monitoring, logging, and tracing solutions (Observability/Telemetry).
Mentor other peers and team members throughout the development and rollout process to improve and sustain technical excellence.
Act as a point of contact for cross-functional partners; analyze past incidents and proactively develop software solutions to prevent recurrence. Build automation to accelerate incident detection, diagnosis, and resolution.

We're looking for a Senior AI Engineer to design, build, and ship production-grade LLM agents that reason over workforce and skills data on top of Loomra's semantic layer. You won't just prototype - you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily (Teams, Slack, Copilot), and iteration in front of enterprise customers. You'll work alongside product, data, and platform engineers to turn powerful capabilities into reliable, safe, and fast product experiences.
If you've built agents that actually made it to production - and you care as much about evaluation, guardrails, and reliability as you do about capability - we want to talk to you.
Responsibilities
Design and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents.
Implement retrieval and RAG pipelines over structured and unstructured workforce data, grounded in our knowledge graph connecting people, jobs, and skills.
Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows.
Build evaluation harnesses, guardrails, and safety/bias checks, and work within the governance engine so agents behave reliably, respect customer policies, and produce a full audit trail.
Ship agents in a model-agnostic way across providers (Anthropic, Google, IBM watsonx) and deploy them into Teams, Slack, and Copilot.
Optimize agents for latency, cost, and reliability at enterprise scale.
Take agents from prototype to production - with monitoring, observability, and a fast iteration loop.
Partner closely with product, data, and platform teams to translate customer needs into agent capabilities.

Required Senior Data & ML Infrastructure Engineer
What will your job look like?
Optimize distributed data and evaluation pipelines for memory efficiency, throughput, and training performance.
Build tools for data exploration, manipulation, validation, and quality assessment.
Own model manipulation, packaging, distribution workflows, and interfaces with downstream deployment and EyeQ integration.
Coordinate data contracts and workflows with researchers, infrastructure and data teams, and internal customers across.

We are looking for a Senior Software Engineer to join a high-performing team of engineers shaping the future of cloud security.
This is a unique opportunity to work on a next-generation SaaS platform, tackling complex engineering challenges in distributed systems, scalability, and performance, while collaborating with top engineers, researchers, and product leaders.
If you are passionate about building systems from the ground up, love working with cloud-native technologies, and want to make a real impact - this role is for you.
What You Will Own:
Design and build core backend systems and infrastructure powering Aquas SaaS platform
Develop scalable, multi-tenant microservices in a cloud-native environment
Take full end-to-end ownership - from design and development to production and monitoring
Collaborate with Engineering, Product, and Security Research teams to solve complex cybersecurity challenges
Build and optimize distributed, event-driven systems at scale
Work in a modern CI/CD environment with cutting-edge technologies
Lead and execute PoCs and technology evaluations
Partner with customers and internal stakeholders to deliver impactful solutions
Continuously improve performance, scalability, and reliability