обновлено 4 дня назад
Senior Solutions Engineer (Big Data)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Solutions Engineer (Big Data): Building and optimizing scalable data infrastructure and pipelines for real-time data analysis and AI applications with an accent on hybrid cloud environments and distributed systems. Focus on designing robust solutions, collaborating with cross-functional teams, and ensuring high performance and reliability.
Location: Tel Aviv, Israel
Company
builds enterprise data management infrastructure for AI, including platforms for capturing, cataloging, refining, enriching, protecting, and serving massive datasets across data centers, edge environments, and cloud.
What you will do
- Build distributed data pipelines with Kafka, Spark, Python, Trino, Airflow, and S3-compatible data lakes for batch and real-time workloads.
- Design, deploy, and troubleshoot hybrid cloud and on-premises environments using Terraform, Docker, Kubernetes, and CI/CD automation.
- Implement event-driven and serverless workflows while balancing latency, throughput, and fault tolerance.
- Own the platform lifecycle from ingestion and transformation through S3-based storage and Trino/Spark compute.
- Benchmark and tune S3, NFS, and SMB storage backends and analytics engines using production datasets.
- Create architecture documentation, technical guides, and demo pipelines while collaborating with engineering, product, R&D, and customers.
Requirements
- 2–4 years of experience in software, solutions, or infrastructure engineering, including experience with large-scale data pipelines, storage, or database solutions.
- Proficiency in Trino and Spark, including Structured Streaming and batch processing, plus solid knowledge of Apache Kafka.
- Strong Python programming skills; Bash and scripting experience is beneficial.
- Understanding of SQL, NoSQL, HDFS, distributed systems, stream processing, and event-driven architecture.
- Experience with Docker, Kubernetes, Terraform, benchmarking, and performance profiling for storage systems, databases, or analytics engines.
- Strong communication skills for explaining technical concepts, guiding customer discussions, and collaborating across engineering and product teams.
Culture & Benefits
- Work on infrastructure designed for enterprise AI training, inference, and real-time analytics.
- Collaborate with internal engineering and product groups as well as external customers.
- Contribute to a customer-focused environment centered on technical innovation and measurable market impact.
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