לוח משרות דרושים איש ביג דאטה Big Data במרכז

We are looking for developers interested in joining exciting and innovative bigdata projects
This is a great opportunity for individuals seeking to develop solutions to the most challenging problems in the bigdata field, dealing with operational requirements while using cutting edge technologies.

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 infrastructuresomeone 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 stacksits 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 lakesdesigned 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 storebacked data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

This role provides the opportunity to lead end-to-end design & implementation of advanced server-side features using a wide range of technologies: Apache Spark, Apache Airflow, Scala, k8s, Node.js (JS/Typescript) with MongoDB, Redis, Kafka, Dockers and Flink (Big Data Stream Processing)

If you are up for the challenge and you have the XM factor, come and join us!

Were looking for a Big Data Engineer who loves turning massive, messy datasets into scalable, reliable systems. Youll design and maintain data pipelines, ensure data quality, and collaborate with data scientists and product managers to bring new insights to life.

What youll do:
Design, build, and optimize scalable data pipelines and ETL processes
Own data products from design to production.
Ensure data accuracy, integrity, and performance across large datasets.
Collaborate with data scientists and engineers to deliver production-grade experiment.

As part of the Data Infrastructure group, youll help build Lemonades data platform for our growing stack of products, customers, and microservices.

We ingest our data from our operational DBs, telematics devices, and more, working with several data types (both structured and unstructured). Our challenge is to provide building tools and infrastructure to empower other teams leveraging data-mesh concepts.

In this role youll:
Help build Lemonades data platform, designing and implementing data solutions for all application requirements in a distributed microservices environment

Build data-platform ingestion layers using streaming ETLs and Change Data Capture

Implement pipelines and scheduling infrastructures

Ensure compliance, data-quality monitoring, and data governance on data platform

Implement large-scale batch and streaming pipelines with data processing frameworks

Collaborate with other Data Engineers, Developers, BI Engineers, ML Engineers, Data Scientists, Analysts and Product managers

Share knowledge with other team members and promote engineering standards

We are looking for a talented and dedicated ML & Big Data Analyst who will be a part of the Core Data group.
As part of this role, you will help us process and streamline rich and complicated datasets. Will explore and validate new data sources. Be part of the data science and data engineering force creating new features for our solution.
What does the day-to-day of a ML & Big Data Analyst at our company look like:
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools that will ensure the quality of our companys data and algorithms.
Utilize your deep understanding of our companys data in order to evaluate and improve novel algorithms produced by the data scientists in your team.
Partner with Big Data Engineers to establish an infrastructure to scale solutions.

We are seeking an experienced Data Platform Engineer to join our Storage Analytics team. You will design and build data solutions that provide critical insights into storage performance and usage across Apple's entire device ecosystem.
Description:
Working with large-scale telemetry data from millions of Apple devices worldwide, you'll support multiple CoreOS Storage teams, including Software Update, Backup/Restore/Migration, Storage Attribution, and other storage domains.
Responsibilities
Design, build, and maintain scalable data processing infrastructure to handle large-scale telemetry from Apple's global device fleet
Develop highly scalable data pipelines to ingest and process storage performance metrics, usage patterns, and system telemetry with actionable alerting and anomaly detection
Build and maintain robust data platforms and ETL frameworks that enable CoreOS Storage teams to access, process, and derive insights from storage telemetry data
Engineer automated data delivery systems and APIs that serve processed storage metrics to various engineering teams across different storage domains