דרושים » תוכנה » לחברת SaaS בתל אביב דרוש /ה Senior data engineer.

Were looking for a Big Data Engineer to develop and integrate systems that retrieve, process and analyze data from around the digital world, generating customer-facing data. This role will report to our Team Manager, R&D.
Why is this role so important?
we are a data-focused company, and data is the heart of our business.
As a big data engineer developer, you will work at the very core of the company, designing and implementing complex high scale systems to retrieve and analyze data from millions of digital users.
Your role as a big data engineer will give you the opportunity to use the most cutting-edge technologies and best practices to solve complex technical problems while demonstrating technical leadership.

In this role, youll own the engineering backbone that enables our data engineers & data scientists to experiment, innovate, and deploy production-ready models, ensuring our systems are robust, scalable, and future-proof.

What You'll Actually Do:

Lead and mentor a team of Data Engineers, fostering a culture of technical excellence, accountability, and collaboration.
Define and drive the teams technical roadmap, standards, and best practices for data modeling, performance, and reliability.
Design, build, and evolve scalable embedding pipelines and recommendation infrastructure, from algorithm tuning and training workflows to production deployment.
Manage and optimize vector db, ensuring efficient indexing strategies, search performance, and low-latency retrieval.
Lead the development of retrieval services leveraging Approximate Nearest Neighbor (ANN/KNN) techniques such as HNSW, IVF, and Product Quantization (PQ).
Ensure reliability, observability, and scalability across all real-time data systems powering our recommendation engine.
Collaborate with Data Science, Product, and Analytics to operationalize models, validate KPIs, and translate technical insights into actionable product improvements.

It starts with you - an engineer driven to build modern, real-time data platforms that help teams move faster with trust. You care about great service, performance, and cost. Youll architect and ship a top-of-the-line open streaming data lake/lakehouse and data stack, turning massive threat signals into intuitive, self-serve data and fast retrieval for humans and AI agents - powering a unified foundation for AI-driven mission-critical workflows across cloud and on-prem.
If you want to make a meaningful impact, join mission and build best-in-class data systems that move the world forward - this role is for you.
:Responsibilities
Build self-serve platform surfaces (APIs, specs, CLI/UI) for streaming and batch pipelines with correctness, safe replay/backfills, and CDC.
Run the open data lake/lakehouse across cloud and on-prem; enable schema evolution and time travel; tune partitioning and compaction to balance latency, freshness, and cost.
Provide serving and storage across real-time OLAP, OLTP, document engines, and vector databases.
Own the data layer for AI - trusted datasets for training and inference, feature and embedding storage, RAG-ready collections, and foundational building blocks that accelerate AI development across the organization.
Enable AI-native capabilities - support agentic pipelines, self-tuning processes, and secure sandboxing for model experimentation and deployment.
Make catalog, lineage, observability, and governance first-class - with clear ownership, freshness SLAs, and access controls.
Improve performance and cost by tuning runtimes and I/O, profiling bottlenecks, planning capacity, and keeping spend predictable.
Ship paved-road tooling - shared libraries, templates, CI/CD, IaC, and runbooks - while collaborating across AI, ML, Data Science, Engineering, Product, and DevOps. Own architecture, documentation, and operations end-to-end.