לוח משרות דרושים איש ביג דאטה Big Data

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

Shape the Future of Data - Join our mission to build the foundational pipelines and tools that power measurement, insights, and decision-making across our product, analytics, and leadership teams.
Develop the Platform Infrastructure - Build the core infrastructure that powers our data ecosystem including the Kafka events-system, DDL management with Terraform, internal data APIs on top of Databricks, and custom admin tools (e.g. Django-based interfaces).
Build Real-time Analytical Applications - Develop internal web applications to provide real-time visibility into platform behavior, operational metrics, and business KPIs integrating data engineering with user-facing insights.
Solve Meaningful Problems with the Right Tools - Tackle complex data challenges using modern technologies such as Spark, Kafka, Databricks, AWS, Airflow, and Python. Think creatively to make the hard things simple.
Own It End-to-End - Design, build, and scale our high-quality data platform by developing reliable and efficient data pipelines. Take ownership from concept to production and long-term maintenance.
Collaborate Cross-Functionally - Partner closely with backend engineers, data analysts, and data scientists to drive initiatives from both a platform and business perspective. Help translate ideas into robust data solutions.
Optimize for Analytics and Action - Design and deliver datasets in the right shape, location, and format to maximize usability and impact - whether thats through lakehouse tables, real-time streams, or analytics-optimized storage.
You will report to the Data Engineering Team Lead and help shape a culture of technical excellence, ownership, and impact.