ABOUT THE ROLE
We are looking for a Senior Data Engineer with strong Python expertise and extensive experience building large-scale, distributed data systems.
You will play a key role in developing our next-generation data platform, building integrations with external data sources, and designing the services and pipelines that collect, process, and serve large volumes of data across our product.
You will own systems throughout their full lifecycle — from system design and hands-on development to deployment, scalability, and production monitoring — while contributing to technical decisions and working closely with the team on building reliable, high-performance data solutions.
Our Office is located in Kiryat Ono.This is a hybrid position, including two work-from-home days per week, with flexibility .
Requirements
5+ years of professional software/data engineering experience, with strong hands-on Python proficiency.
Proven experience building and maintaining large-scale, data-intensive systems in production.
Strong SQL skills, including working with large and complex datasets, query optimization, and data modeling.
Hands-on experience designing and developing data pipelines and services that process data asynchronously or in batches.
Solid understanding of distributed-system fundamentals, including failure handling, retries, idempotency, concurrency, and eventual consistency.
Experience contributing to system design and technical decisions around scalable, reliable data systems.
Experience building and consuming REST APIs and integrating with third-party systems. Experience with FastAPI, Django, Flask, or similar frameworks is an advantage.
Strong problem-solving skills and the ability to investigate unfamiliar systems and complex data flows.
Ability to work independently, take ownership, make sound engineering decisions, and collaborate effectively within a small, highly technical team.
Advantage
Experience working with high-volume data processing and distributed data infrastructure.
Nice to Have-
Experience with Amazon Redshift or another analytical data warehouse.
Familiarity with Docker, CI/CD, logging, monitoring, and troubleshooting production systems
Experience building ETL or ELT pipelines and implementing data-quality checks.
Experience with queues, schedulers, or workflow orchestration tools.
Familiarity with infrastructure as code and cloud infrastructure management.
Experience with high-volume data ingestion, analytics platforms, marketing technology, or campaign-management systems.
Responsibilities
Build and improve data-collection and processing workflows, including scheduled, asynchronous, and long-running workloads.
Develop reliable integrations with external APIs, platforms, and data providers.
Design, build, and maintain backend services using Python and FastAPI.
Contribute to our new platform and capabilities such as algorithm execution and data collection orchestration.
Design efficient data models and queries for operational databases and analytical systems such as Amazon Redshift.
Handle real-world integration challenges including rate limits, retries, partial failures, idempotency, and changing external schemas.
Improve the performance, scalability, observability, and reliability of existing services.
Own features end to end: technical design, implementation, testing, deployment, monitoring, and ongoing improvement.
Collaborate with product and engineering colleagues to turn ambiguous requirements into pragmatic technical solutions.
