Senior Data Engineer

Prisma Photonics

. Design data collection processes for textual and multidimensional data .

Posted 11/4/2026full-timeTel Aviv • IsraelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing data pipelines, optimizing data storage, and ensuring efficient data access for AI and algorithms teams. Proficient in collaboration with cross-functional teams and utilizing advanced data technologies for enhanced data analysis and reporting.

Highest-signal resume keywords

Data Pipeline DevelopmentSQL And NoSQL DatabasesApache Airflow Or PrefectPython ProgrammingKubernetes-Based Systems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Collection ProcessesData Storage OptimizationData Schema AnalysisEvent-Driven ModelsAsynchronous MessagingStreaming TechnologiesHadoopMapReduceSparkData Visualization Tools

Soft Skills

CollaborationInnovative MindsetWillingness To Learn

Tools & Technologies

KafkaRabbitMQMySQLElasticsearchMongoDBPostgreSQLClickHouseGitDockerCI/CD Pipelines

Industry Keywords

Data EngineeringCloud ComputingData Access APIsLow-Latency AccessData Pipelines

Tech Stack

Tools & technologies

AirflowApacheCloudDockerElasticSearchGrafanaHadoopKafkaKubernetesMapReduceMongoDBMySQLNoSQLPostgresPythonRabbitMQSparkSQL

About the role

Key responsibilities & impact

Design data collection processes for textual and multidimensional data
Implement data searches and access APIs between edge computing and the cloud stack
Develop and optimize data and metadata storage and databases so AI and Algorithms teams can efficiently access training and test data
Analyze existing data schemas and processes and implement improvements
Analyze cloud data usage and optimize cost structures while maintaining low-latency access through common and proprietary services
Collaborate with Software, AI, and Algorithms teams on system integration, ongoing data requests, and data access
Build and maintain optimized, highly available data pipelines for deeper analysis and reporting

Requirements

What you’ll need

5+ years of professional experience in data engineering or related roles, including hands-on experience designing and implementing data pipelines using orchestration frameworks such as Apache Airflow or Prefect
Experience with event-driven models and asynchronous messaging, including Kafka and RabbitMQ
5+ years of experience and deep understanding of SQL and NoSQL databases, including MySQL, Elasticsearch, MongoDB, PostgreSQL, and ClickHouse
5+ years of software development experience, including 2+ years with Python
Full control of version control systems such as Git, containerization such as Docker, and CI/CD pipelines
Experience with streaming technologies, unstructured data, and data types other than text and tables
Experience with Hadoop, MapReduce, Spark, or other distributed computing platforms
Experience with Kubernetes-based systems
Experience with data visualization and analysis tools such as Grafana, ELK, and Kibana
Strong collaboration with teams and peers
Innovative mindset and willingness to learn and grow