דרושים » דאטה » Data Platform Engineer

Required Data Engineer
Description
Join our core platform engineering team, developing our AI-powered automotive data management platform.
We are developing the next generation data-driven products for the Automotive industry, focusing on cybersecurity (XDR) and vehicle quality. Our products monitor and secure millions of vehicles worldwide and help automakers leverage connected vehicle data to deliver cyber resilience, safety, customer satisfaction and increase brand loyalty.
Our Data Engineering & Data Science Group leads the development of our Iceberg-based data platform, including data lake, query engine, and ML-Ops tools, serving as a solid AI-ready foundation for all our products.
At the core of our Engineering Team, you will build and operate scalable, production-grade customer-facing data and ML platform components, focusing on reliability and performance.
Technological background and focus: Iceberg, Trino, Prefect, GitHub Actions, Kubernetes, JupyterHub, MLflow, dbt
This role is full-time and is Herzliya, Israel based.
Responsibilities
Design, build, and maintain scalable data pipelines to ingest and transform batch data on our data lake, enabling analytics and ML with strong data quality, governance, observability, and CI/CD.
Build and expand our foundational data infrastructure, including our data lake, analytics engine, and batch processing frameworks.
Create robust infrastructure to enable automated pipelines that will ingest and process data into our analytical platforms, leveraging open-source, cloud-agnostic frameworks and toolsets.
Develop and maintain our data lake layouts and architectures for efficient data access and advanced analytics.
Build our ML platform and automate the ML lifecycle.
Drive business-wide ML projects from an engineering perspective.
Develop and manage orchestration tools, governance tools, data discovery tools, and more.
Work with other team members of the engineering group, including data architects, data analysts, and data scientists, to provide solutions using a use case-based approach that drives the construction of technical data flows.

We are looking for a Data Platform Engineer.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Key Responsibilities:
Design and implement scalable data processing pipelines using Azure Databricks and other modern data platforms to power real-time analytics and insights.
Push boundaries by pioneering new technologies and stretching existing ones to their limitsbe a trailblazer in data innovation.
Design, build, and maintain scalable data processing and analytics infrastructure and pipelines, optimizing for performance and cost efficiency.
Collaborate cross-functionally with software engineering, product, and research teams to understand data needs and ensure data solutions meet business requirements.
Engage with strategic customers, ensuring our data solutions meet high standards and deliver measurable value in real-world environments.

We are seeking a skilled ML Engineer to design, build, and deploy advanced ML solutions that drive analytics, anomaly detection, and data classification across enterprise-scale environments.
This role will focus on developing and optimizing models, including LLMs and prompt engineering pipelines, and ensuring seamless integration into production workflows spanning cloud-native, on-premises, and Databricks ecosystems.
Key Responsibilities :
Design, build, and deploy ML models for user behavior analytics, anomaly detection, and data classification across enterprise environments.
Collaborate with data scientists, software and data engineers to integrate ML models into production pipelines, cloud-native environments, on-premises, and Databricks workflows.
Develop, fine-tune, and evaluate LLMs and prompt engineering solutions for data classification, labeling, and threat analysis features.
Optimize models using techniques like distillation, quantization, and efficient data structures to boost performance and lower resource cost.
Build high-performance data inputs using embeddings, vector databases, and distributed training frameworks.
Manage model lifecycle and performance via MLOps best practices: monitoring, retraining, and deploying updates.
Partner with data scientists, cybersecurity researchers and product teams to evaluate and refine ML-driven capabilities.
Conduct experiments and benchmark results in fast-paced, data-intensive environments.

We are seeking a Big Data Engineer with at least 3 years of experience. A strong understanding of data structure is critical.
You will design, develop and maintain data systems, optimize pipelines, and ensure data integrity.
Data Engineers shape and improve leading mobile analytics solutions while using cutting edge technologies such as Scala, Spark, Hadoop, Astronomer, BigQuery, and many more.
What youll do
Own and develop our products and features end-to-end - from design to production
Collaborate with Product Managers and Software Engineers to deliver complex products.
Develop and maintain scalable data pipelines.
Implement ETL processes and data integration.
Optimize data performance and ensure security.

We are looking for a skilled and motivated Big Data Engineer to join our backend data infrastructure team. You will be at the core of Finals data ecosystem, building and maintaining high-performance data services and pipelines that support both real-time and batch workloads. Your work will directly impact how data is accessed and leveraged across the company from live production environments to ML training pipelines. You will design and maintain systems that span hybrid infrastructure (on-prem and cloud), and ensure our data platform is fast, reliable, and scalable. We value engineers who are curious, open-minded, and excited to learn new technologies and practices as the landscape evolves.



As a Big Data Engineer, you will:

Design, implement, and maintain backend services for managing and processing large-scale data.
Build and operate production-grade data pipelines and infrastructure.
Develop utilities ,libraries and services to support high-throughput data retrieval and access patterns.
Ensure observability, stability, and performance of data services in hybrid (cloud/on-prem) environments.
Monitor and troubleshoot issues in live systems and continuously improve their robustness.
Work cross-functionally to ensure data is accessible, well-modeled, and easy to consume by other teams.

We are looking for a ML Engineer.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Responsibilities:
Design, build, and deploy ML models for user behavior analytics, anomaly detection, and data classification across enterprise environments.
Collaborate with data scientists, software and data engineers to integrate ML models into production pipelines, cloud-native environments, on-premises, and Databricks workflows.
Develop, fine-tune, and evaluate LLMs and prompt engineering solutions for data classification, labeling, and threat analysis features.
Optimize models using techniques like distillation, quantization, and efficient data structures to boost performance and lower resource cost.
Build high-performance data inputs using embeddings, vector databases, and distributed training frameworks.
Manage model lifecycle and performance via MLOps best practices: monitoring, retraining, and deploying updates.
Partner with data scientists, cybersecurity researchers and product teams to evaluate and refine ML-driven capabilities.
Conduct experiments and benchmark results in fast-paced, data-intensive environments.

We are looking for a talented Algorithm Engineer to join our Cognitive AI team. In this role, you will design, build, and optimize LLM-based agents that power real-time problem solving. You will be hands-on in Python, research-driven, and passionate about creating intelligent, scalable AI solutions that make a real impact.
Responsibilities:
Design, develop, and optimize LLM-based agents for real-world production use cases.
Build intelligent agent frameworks that orchestrate reasoning across tools, APIs, and knowledge bases.
Deploy and maintain LLM applications in production, ensuring performance, scalability, and reliability.
Research new approaches in LLMs and agent architectures, and integrate cutting-edge techniques into production systems.
Collaborate with cross-functional teams (product, engineering, data) to translate business needs into AI solutions.
Continuously monitor and optimize deployed models, diagnosing and resolving bottlenecks.
Think creatively about complex problems and deliver technological Innovation

At CodeValue , we specialize in delivering cutting-edge software solutions and driving innovation across industries. We are now looking for a Data Engineer to join our team and play a key role in building and optimizing large-scale Big Data systems in production environments.
Key Responsibilities
* Design, implement, and maintain Big Data pipelines in production.
* Work extensively with Apache Spark (2.x and above) , focusing on complex joins, shuffle optimization, and performance improvements at scale.
* Integrate Spark with relational databases, NoSQL systems, cloud storage, and streaming platforms
* Contribute to system architecture and ensure scalability, reliability, and efficiency in data processing workflows.

We are looking for a talented and experienced big data engineer to join our cyber defence group to take over a cutting-edge data solution.
The successful candidate should have hands-on experience with big data processing technologies and architectures.
The candidate will join our growing team of analysts, developers, data scientists, and architects who design and develop innovative solutions to the most critical needs of our customers.
Responsibilities
Designing, architecting, implementing, and supporting our data pipelines and processing flows.
Collaborate with analytics department to analyze and understand data sources.+
Provide insights and guidance on database technology and data modelling best practices.
Insure the maintenance of data integrity, managing data and analysis flows with attention to detail and high responsibility.
Implementing algorithms with our data scientists.

Required Senior Data Engineer
As part of the Audiences team, youll work on highly scalable systems, tackle real-time challenges, and contribute to a platform that directly impacts the success of our customers campaigns.
Our team mixes disciplines from back-end, data, AI and front-end engineers and were looking for a great back-end data oriented developer that is passionate about what they do, who want to dive into the worlds of big data, microservices and production management at our scale, to help us reach our vision and goals
What youll do
Solve diverse, complex problems at a large scale
Collaborate with Product Managers, data scientists and Software Engineers to deliver innovative, user-facing products.
Independent - cradle to grave, own a feature from scratch to production
Analyze and improve performance, scalability and stability of our products, environments and tools
Continuously learn and evaluate new technologies in the everlasting effort to perfect our products and adapt to the ever-growing scale.