לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER משרה מלאה

We are looking for a Senior Data Platform Engineer to design, build, and scale next-generation data platform, the backbone powering our AI-driven insights.
This role sits at the intersection of data engineering, infrastructure, and MLOps, owning the architecture and reliability of our data ecosystem end-to-end.
Youll work closely with data scientists,r&d teams, analysts to create a robust platform that supports varying use cases, complex ingestion, and AI-powered analytics.
Responsibilities:
Architect and evolve a scalable, cloud-native data platform that supports batch, streaming, analytics, and AI/LLM workloads across R&D.
Help define and implement standards for how data is modeled, stored, governed, and accessed
Design and build data lakes and data warehouses
Develop and maintain complex, reliable, and observable data pipelines
Implement data quality, validation, and monitoring frameworks
Collaborate with ML and data science teams to connect AI/LLM workloads to production data pipelines, enabling RAG, embeddings, and feature engineering flows.
Manage and optimize relational and non-relational datastores (Postgres, Elasticsearch, vector DBs, graph DBs).
Build internal tools and self-service capabilities that enable teams to easily ingest, transform, and consume data.
Contribute to data observability, governance, documentation, and platform visibility
Drive strong engineering practices
Evaluate and integrate emerging technologies that enhance scalability, reliability, and AI integration in the platform.

We are seeking an experienced Data Engineer with a strong background in BI and Data Engineering, excellent problem-solving skills, and the ability to work independently and learn quickly.
Role Overview
You will join a dynamic team responsible for designing and implementing end-to-end data solutions on the Microsoft Fabric platform. This role involves:
Building and maintaining robust data processes.
Driving adoption of new technology within the organization.
Ensuring scalability, performance, and reliability of data solutions.
Responsibilities:
Collaborate with leaders, stakeholders, and product managers to understand data requirements and deliver effective BI solutions.
Design, develop and maintain robust data pipelines for efficient data ingestion, processing, and storage.
Optimize data storage and retrieval processes for optimal performance.
Monitor data pipelines and systems consistently to identify performance issues, ensuring timely maintenance and troubleshooting.
Create and maintain documentation of data processes and systems.

we are looking for a Data 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 maintain scalable ETL/ELT pipelines to integrate data from diverse sources, optimizing for performance and cost efficiency.
Leverage Databricks and other modern data platforms to manage, transform, and process data
Collaborate with software teams to understand data needs and ensure data solutions meet business requirements.
Optimize data processing workflows for performance and scalability.

We are looking for an experienced Data Engineering Team Leader.
In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data and analytics platforms.
A day in the life and how youll make an impact:
Drive the technical strategy and roadmap for the data engineering function, ensuring alignment with overall business objectives.
Own the design, development, and evolution of scalable, high-performance data pipelines to enable diverse and growing business needs.
Establish and enforce a strong data governance framework, including comprehensive data quality standards, monitoring, and security protocols, taking full accountability for data integrity and reliability.
Lead the continuous enhancement and optimization of the data analytics platform and infrastructure, focusing on performance, scalability, and cost efficiency.
Champion the complete data lifecycle, from robust infrastructure and data ingestion to detailed analysis and automated reporting, to maximize the strategic value of data and drive business growth.

The ideal candidate is not afraid of data in any form or scale, and is experienced with cloud services to ingest, stream, store, and manipulate data. The Data Engineer will support new system designs and migrate existing ones, working closely with solutions architects, project managers, and data scientists. The candidate must be self-directed, a fast learner, and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing or re-designing our customers data architecture to support their next generation of products, data initiatives, and machine learning systems.





Summary of Key Responsibilities



To meet compliance and regulatory requirements, keep our customers data separated and secure.
Design, Build, and operate the infrastructure required for optimal data extraction, transformation, and loading from a wide variety of data sources using SQL, cloud migration tools, and big data technologies.
Optimize various RDBMS engines in the cloud and solve customers' security, performance, and operational problems.
Design, build, and operate large, complex data lakes that meet functional / non-functional business requirements.
Optimize various data types' ingestion, storage, processing, and retrieval, from near real-time events and IoT to unstructured data such as images, audio, video, documents, and in between.
Work with customers' and internal stakeholders including the Executive, Product, Data, Software Development and Design teams to assist with data-related technical issues and support their data infrastructure and business needs.

Are you a person who likes to work in a fast paced organization? For two decades, our company has pioneered visual computing, the art and science of computer graphics. With our invention of the GPU - the engine of modern visual computing - the field has expanded to encompass personal computer games, movie production, product design, medical diagnosis and scientific research. Today, visual computing is becoming increasingly central to how people harmonize with technology, and there has never been a more exciting time to join our excellent team. we are now passionate about innovation at the intersection of visual processing, high performance computing, and artificial intelligence.
Our data centers, and the thousands of servers installed in them, are the foundation upon which our creative products and services are delivered. Our customer base consists of hundreds of deeply intelligent engineers who continually provide us with complex problems to be solved. We are looking for a highly motivated Data Center Engineer to join our team. Having depth and breadth knowledge of working in data center facilities in a large-scale distributed environment is a strength you'll need. You should have deep knowledge and experience in at least one of the following core areas: Project Management, Hardware Operations, Network Operations or Data Center Operations.
What you'll be doing:
Act as technical liaison for our technical teams.
Project manage highly impactful large and small scale data center and lab projects.
Participate in the installation, monitoring, maintenance, support, and optimization of all production server hardware.
Contribute to the development of the global DC knowledge base
Lead teams to deploy new data center infrastructure, deliver server upgrades, integration, rebuild and other projects as required
Build plans to optimize power, cooling and network resources
Inventing the forecast to efficiently match supply to demand. Predict data center growth and scaling issues before they occur and implement solutions. You will acquire new facilities and optimize existing ones to support the business growth.
You will hunt for and resolve issues as well as analyze data looking for trends and systemic issues. Implement process improvements and develop a cutting edge operational environment.

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 an expert Data Engineer to build and evolve the data backbone for our R&D telemetry and performance analytics ecosystem. Responsibilities include processing raw, large quantities of data from live systems at the cluster level: hardware, communication units, software, and efficiency indicators. Youll be part of a fast paced R&D organization, where system behavior, schemas, and requirements evolve constantly. Your mission is to develop flexible, reliable, and scalable data handling pipelines that can adapt to rapid change and deliver clean, trusted data for engineers and researchers.
What youll be doing:
Build flexible data ingestion and transformation frameworks that can easily handle evolving schemas and changing data contracts
Develop and maintain ETL/ELT workflows for refining, enriching, and classifying raw data into analytics-ready form
Collaborate with R&D, hardware, DevOps, ML engineers, data scientists and performance analysts to ensure accurate data collection from embedded systems, firmware, and performance tools
Automate schema detection, versioning, and validation to ensure smooth evolution of data structures over time
Maintain data quality and reliability standards, including tagging, metadata management, and lineage tracking
Enable self-service analytics by providing curated datasets, APIs, and Databricks notebooks.

Welcome to Chargeflow Chargeflow is at the forefront of fintech + AI innovation, backed by leading venture capital firms. Our mission is to build a fraud-free global commerce ecosystem by leveraging the newest technology, freeing online businesses to focus on their core ideas and growth. We are building the future, and we need you to help shape it. Who We're Looking For - The Dream Maker We're in search of an experienced and skilled Senior Data Engineer to join our growing data team. As part of our data team, you'll be at the forefront of crafting a groundbreaking solution that leverages cutting-edge technology to combat fraud. The ideal candidate will have a strong background in designing and implementing large-scale data solutions, with the potential to grow into a leadership role. This position requires a deep understanding of modern data architectures, cloud technologies, and the ability to drive technical initiatives that align with business objectives. Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to safeguard their revenue and optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud. Your Arena
* Design, develop, and maintain scalable, robust data pipelines and ETL processes
* Architect and implement complex data models across various storage solutions
* Collaborate with R&D teams, data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality solutions
* Ensure data quality, consistency, security, and compliance across all data systems
* Play a key role in defining and implementing data strategies that drive business value
* Contribute to the continuous improvement of our data architecture and processes
* Champion and implement data engineering best practices across the R&D organization, serving as a technical expert and go-to resource for data-related questions and challenges
* Participate in and sometimes lead code reviews to maintain high coding standards
* Troubleshoot and resolve complex data-related issues in production environments
* Evaluate and recommend new technologies and methodologies to improve our data infrastructure