דרושים » דאטה » Senior Data Engineer

The Audiences team is responsible for building and maintaining our industry leading segmentation solution. Enabling customers to define, manage, and activate dynamic user segments across multiple advertising platforms.

We handle complex data pipelines, real-time audience updates, and seamless integrations with major media partners. Were also building predictive audience capabilities using AI to help our customers target the right users before they take action. Our work plays a critical role in driving user acquisition, engagement, and retention strategies for some of the worlds largest brands.

As part of the Audiences team, youll work on highly scalable systems, tackle real-time challenges, and contribute to a platform that directly impacts the success of our customers campaigns.

Our team mixes disciplines from back-end, data, AI and front-end engineers and were looking for a great back-end data oriented developer that is passionate about what they do, who want to dive into the worlds of big data, microservices and production management at our scale, to help us reach our vision and goals

What youll do
Solve diverse, complex problems at a large scale
Collaborate with Product Managers, data scientists and Software Engineers to deliver innovative, user-facing products.
Independent - cradle to grave, own a feature from scratch to production
Analyze and improve performance, scalability and stability of our products, environments and tools
Continuously learn and evaluate new technologies in the everlasting effort to perfect our products and adapt to the ever-growing scale

Required Senior Data Engineer
Description
Join our core platform engineering team, developing our AI-powered automotive data management platform.
We are developing the next generation data-driven products for the Automotive industry, focusing on cybersecurity (XDR) and vehicle quality. Our products monitor and secure millions of vehicles worldwide and help automakers leverage connected vehicle data to deliver cyber resilience, safety, customer satisfaction and increase brand loyalty.
Our Data Engineering & Data Science Group leads the development of our Iceberg-based data platform, including data lake, query engine, and ML-Ops tools, serving as a solid AI-ready foundation for all our products.
At the core of our Engineering Team, you will build and operate scalable, production-grade customer-facing data and ML platform components, focusing on reliability and performance.
Technological background and focus: Iceberg, Trino, Prefect, GitHub Actions, Kubernetes, JupyterHub, MLflow, dbt
This role is full-time and is Herzliya, Israel based.
Responsibilities
Design, build, and maintain scalable data pipelines to ingest and transform batch data on our data lake, enabling analytics and ML with strong data quality, governance, observability, and CI/CD.
Build and expand our foundational data infrastructure, including our data lake, analytics engine, and batch processing frameworks.
Create robust infrastructure to enable automated pipelines that will ingest and process data into our analytical platforms, leveraging open-source, cloud-agnostic frameworks and toolsets.
Develop and maintain our data lake layouts and architectures for efficient data access and advanced analytics.
Build our ML platform and automate the ML lifecycle.
Drive business-wide ML projects from an engineering perspective.
Develop and manage orchestration tools, governance tools, data discovery tools, and more.
Work with other team members of the engineering group, including data architects, data analysts, and data scientists, to provide solutions using a use case-based approach that drives the construction of technical data flows.

As a Data Engineer , you will own the architecture and optimization of large-scale ETL processes that transform raw heavy-duty vehicle telemetry into production-grade intelligence. You will operate at the intersection of Big Data and AI, building scalable pipelines, enforcing data quality standards, and managing cost-efficiency for a system processing billions of time-series records. You will be a technical owner, collaborating directly with Data Scientists to ensure our fleet intelligence models run reliably in production.
What Youll Do
Architect and build robust ETLs and scalable data pipelines on Databricks and AWS.
Optimize high-throughput ingestion workflows for billions of time-series records, ensuring low latency and data integrity.
Engineer data validation frameworks and automated monitoring to proactively detect anomalies before they impact models.
Drive cost-efficiency by tuning Spark jobs and managing compute resources in a high-volume environment.
Transform raw IoT/telemetry signals into structured, enriched Feature Stores ready for Machine Learning production.
Define best practices for data engineering, CI/CD for data, and lakehouse architecture across the organization.

we are looking for a Data Engineer
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Responsibilities
Design, build, and maintain scalable ETL/ELT pipelines to integrate data from diverse sources, optimizing for performance and cost efficiency.
Leverage Databricks and other modern data platforms to manage, transform, and process data
Collaborate with software teams to understand data needs and ensure data solutions meet business requirements.
Optimize data processing workflows for performance and scalability.

We are now looking for a Data Engineer to join our team and play a key role in building and optimizing large-scale Big Data systems in production environments.

Key Responsibilities:
Design, implement, and maintain Big Data pipelines in production.
Work extensively with Apache Spark (2.x and above), focusing on complex joins, shuffle optimization, and performance improvements at scale.
Integrate Spark with relational databases, NoSQL systems, cloud storage, and streaming platforms.
Contribute to system architecture and ensure scalability, reliability, and efficiency in data processing workflows.

We are seeking an experienced Data Engineer with a strong background in BI and Data Engineering, excellent problem-solving skills, and the ability to work independently and learn quickly.
Role Overview
You will join a dynamic team responsible for designing and implementing end-to-end data solutions on the Microsoft Fabric platform. This role involves:
Building and maintaining robust data processes.
Driving adoption of new technology within the organization.
Ensuring scalability, performance, and reliability of data solutions.
Responsibilities:
Collaborate with leaders, stakeholders, and product managers to understand data requirements and deliver effective BI solutions.
Design, develop and maintain robust data pipelines for efficient data ingestion, processing, and storage.
Optimize data storage and retrieval processes for optimal performance.
Monitor data pipelines and systems consistently to identify performance issues, ensuring timely maintenance and troubleshooting.
Create and maintain documentation of data processes and systems.