לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER בנתניה, לחיפוש זה נמצאו 6 משרות

We're a leading force in the ad tech industry, revolutionizing how brands connect with their audiences. Our platform processes billions of ad impressions daily, generating massive datasets that drive our core business.

We thrive on innovation and seek a Senior Data Infra Engineer to help us build and scale the data infrastructure that powers our insights and analytics.
This is a unique opportunity to work with cutting-edge technologies and make a direct impact on our products.

What will you do?
As a Senior Data Infra Engineer, you'll be a key part of our data platform team, responsible for designing, building, and maintaining robust and scalable data pipelines. You'll work closely with data scientists, analysts, and server side engineers to ensure our data is reliable, accessible, and ready for analysis. Your expertise will be crucial in expanding our data warehouse and data lake capabilities, enabling us to deliver next-generation ad tech solutions.

Your mission will be to:

Develop and Optimize Data Pipelines: Design, build, and maintain ETL/ELT pipelines using Apache Spark to ingest, process, and transform large-scale datasets from various sources.
Manage Cloud Infrastructure: Architect and manage our data infrastructure primarily on Google Cloud Platform (GCP) or Amazon Web Services (AWS). This includes services like BigQuery, S3, GCS, EMR, and AirFlow.
Enhance Data Storage: Improve and manage our data warehouse and data lake solutions, ensuring data quality, consistency, and accessibility for business intelligence and machine learning applications.
Collaborate and Innovate: Partner with cross-functional teams to understand data needs and implement solutions that support new product features and business initiatives.
Ensure Data Integrity: Implement monitoring, alerting, and logging systems to maintain data pipeline health and ensure data accuracy.

We are looking for a Data Science Engineer to design and implement the decision-making logic of our Price Optimizer. You will focus on translating complex business rules into mathematical models and production-ready Python code.

Your primary mission is to build the "brain" of our system. You will work at the intersection of Data Science and Product, ensuring our simulation and optimization engines accurately reflect real-world pricing strategies and market dynamics. While you will write production code, you will rely on our Data Engineers for ETL pipelines orchestration and distributed compute scaling.

Responsibilities:

Implement Business Logic: Translate intricate pricing rules and commercial strategies into robust Python code and mathematical constraints.
Refine Optimization Models: Develop and tune the simulation and revenue management algorithms that drive our pricing recommendations.
Write Clean Code: Contribute high-quality, tested, and maintainable code to the core logic repositories.
Analyze & Improve: Use data to validate model behavior and identify edge cases where business rules clash with algorithmic outputs.
Collaborate: Partner with Solution Architects to define logic requirements and with Data Engineers to integrate your models into the Dagster pipelines.

Were looking for a Principal Backend & Data Engineer to own and evolve the core data-intensive backend architecture of our AI platform. This is a senior individual contributor role with broad architectural responsibility and deep hands-on impact.

You will be a technical authority in building scalable, high-performance backend and data systems that power our AI research engine - working closely with AI scientists, platform engineers, and product leaders. Beyond implementation, you will define technical direction, set engineering standards, and influence how we build and scale data-driven AI systems across the organization.

What Youll Do
Architecture & Technical Ownership

Own the architecture of core backend and data systems that support large-scale, AI-driven computation and inference.
Design and evolve high-performance analytical processing layers handling complex data workloads at scale.
Make and drive long-term architectural decisions across backend, data, and AI integration domains.
Define standards and best practices for performance, scalability, reliability, and data correctness.
Backend & Data Engineering

Design, implement, and optimize data-intensive backend services using Python.
Build and evolve analytical compute pipelines using technologies such as Polars, DuckDB, AirFlow, Iceberg, Spark and other ingestion and processing frameworks.
Collaborate closely with AI scientists to productionize algorithms and embed advanced intelligence into the platform.
Platform & Infrastructure

Architect and maintain containerized systems using Docker and Kubernetes.
Ensure systems are observable, debuggable, and operable in production environments.
Drive performance tuning and cost-efficiency across compute-heavy workloads.
Technical Leadership

Act as a technical authority and thought leader within the engineering organization.
Mentor senior engineers through design reviews, architectural guidance, and hands-on collaboration.
Serve as a force multiplier by unblocking complex technical challenges and raising the overall engineering bar.