דרושים » דאטה » Data Engineer

Now were looking for an experienced Software Engineer to join our Data team. In this key role, you will develop our data platform, working on cloud-based microservices data pipelines. As we are building the company data platform, it has direct impact on our customers and also enabled many of the other groups in the organization. You will also be responsible for building microservices that need to work on big data scale (about 250K records/sec) in a law latency as part of a dynamic team.
Key Responsibilities:
End-to-end development of company massive data infrastructures and services.
Researching new technologies and adapting them for use in the companys product
Working closely with the product, DevOps, and security teams.

We are growing and are looking for a Senior Data Infra Engineer
who value personal and career growth, team-work, and winning!
What your day will look like:
Design, plan, and build all aspects of the platforms data, machine learning (ML) pipelines, and infrastructure.
Build and optimize an AWS-based Data Lake using best practices in cloud architecture, data partitioning, metadata management, and security to support enterprise-scale data operations.
Collaborate with engineers, data analysts, data scientists, and other stakeholders to understand data needs.
Solve challenging data integration problems, utilizing optimal ETL/ELT patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
Lead end-to-end data projects from infrastructure design to production monitoring.

We are looking for a Senior Data Engineer.
As a Senior Data Engineer, youll be more than just a coder - youll be the architect of our data ecosystem. Were looking for someone who can design scalable, future-proof data pipelines and connect the dots between DevOps, backend engineers, data scientists, and analysts.
Youll lead the design, build, and optimization of our data infrastructure, from real-time ingestion to supporting machine learning operations. Every choice you make will be data-driven and cost-conscious, ensuring efficiency and impact across the company.
Beyond engineering, youll be a strategic partner and problem-solver, sometimes diving into advanced analysis or data science tasks. Your work will directly shape how we deliver innovative solutions and support our growth at scale.
Responsibilities:
Design and Build Data Pipelines: Architect, build, and maintain our end-to-end data pipeline infrastructure to ensure it is scalable, reliable, and efficient.
Optimize Data Infrastructure: Manage and improve the performance and cost-effectiveness of our data systems, with a specific focus on optimizing pipelines and usage within our Snowflake data warehouse. This includes implementing FinOps best practices to monitor, analyze, and control our data-related cloud costs.
Enable Machine Learning Operations (MLOps): Develop the foundational infrastructure to streamline the deployment, management, and monitoring of our machine learning models.
Support Data Quality: Optimize ETL processes to handle large volumes of data while ensuring data quality and integrity across all our data sources.
Collaborate and Support: Work closely with data analysts and data scientists to support complex analysis, build robust data models, and contribute to the development of data governance policies.

Were looking for a Data Engineer to design and implement high-scale, data-intensive platforms, research and develop algorithmic solutions, and collaborate on key company initiatives. You will play a critical role within core data teams, which are responsible for managing and optimizing fundamental data assets.
What will you be responsible for?
Solve Complex Business Problems with Scalable Data Solutions
Develop and implement robust, high-scale data pipelines to power core assets.
Leverage cutting-edge technologies to tackle complex data challenges and enhance business operations.
Collaborate with Business Stakeholders to Drive Impact
Work closely with Product, Data Science, and Analytics teams to define priorities and develop solutions that directly enhance core products and user experience.
Build and Maintain a Scalable Data Infrastructure
Design and implement scalable, high-performance data infrastructure to support machine learning, analytics, and real-time data processing.
Continuously monitor and optimize data pipelines to ensure reliability, accuracy, and efficiency.

Were looking for a Data Engineer for the Insight Team to join Lushas Data Group and a new team responsible for developing innovative features based on multiple layers of data. These features will power recommendation systems, insights, and more. This role involves close collaboration with the core teams within the Data Group, working on diverse data pipelines that tackle challenges related to scale and algorithmic optimization, all aimed at enhancing the data experience for Lushas customers.
What will you be responsible for?
Develop and implement robust, scalable data pipelines and integration solutions within Lushas Databricks-based environment.
Develop models and implement algorithms, with a strong emphasis on delivering high-quality results.
Leverage technologies like Spark, Kafka, and Airflow to tackle complex data challenges and enhance business operations.
Design innovative data solutions that support millions of data points, ensuring high performance and reliability.

we are looking for a Data Engineer to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless company ronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
In this role, you will be responsible for:
Designing, building, and maintaining scalable data pipeline architectures
Developing ETL processes to integrate data from multiple sources
Creating and optimizing data models for efficient storage and retrieval
Implementing data quality controls and monitoring systems
Collaborating with data scientists and analysts to deliver data solutions
Building and maintaining data warehouses and data lakes
Performing in-depth data analysis and providing insights to stakeholders
Taking full ownership of data quality, documentation, and governance processes
Building and maintaining comprehensive reports and dashboards
Ensuring data security and regulatory compliance.

At UVeye, we are on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the world's first fully automated suite of vehicle inspection systems. At the heart of this innovation lies our advanced AI-driven technology, representing the pinnacle of machine learning, GenAI, and computer vision within the automotive sector. With close to $400 million in funding and strategic partnerships with industry giants such as Amazon, General Motors, Volvo, and CarMax, UVeye stands at the forefront of automotive technological advancement. Our growing global team of over 200 employees is committed to creating a workplace that celebrates diversity and encourages teamwork. Our drive for innovation and pursuit of excellence are deeply embedded in our vibrant company culture, ensuring that each individual's efforts are recognized and valued as we unite to build a safer automotive world.
We are looking for an experienced Senior Data Engineer to join our Data team. In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data and analytics platforms.
A day in the life and how you’ll make an impact:
* Design and develop high-performance data pipelines and ETL processes to support diverse business needs.
* Work closely with business intelligence, sales, and other teams to integrate data solutions, ensuring seamless alignment and collaboration across functions.
* Continuously improve our data analytics platforms, optimizing system performance while ensuring a robust and reliable data infrastructure.
* Oversee the entire data lifecycle, from infrastructure setup and data acquisition to detailed analysis and automated reporting, driving business growth through data-driven insights.
* Implement robust data quality checks, monitoring mechanisms, and data governance policies to maintain data integrity and security, troubleshooting and resolving any data-related issues efficiently.

We're seeking talented data engineers to join our rapidly growing team, which includes senior software and data engineers. Together, we drive our data platform from acquisition and processing to enrichment, delivering valuable business insights. Join us in designing and maintaining robust data pipelines, making an impact in our collaborative and innovative workplace.

Responsibilities
Design, implement, and optimize scalable data pipelines for efficient processing and analysis.
Build and maintain robust data acquisition systems to collect, process, and store data from diverse sources.
Take part in developing agentic capabilities.
Collaborate with DevOps, Data Science, and Product teams to understand needs and deliver tailored data solutions.
Monitor data pipelines and production environments proactively to detect and resolve issues promptly.
Apply best practices for data security, integrity, and performance across all systems.

We're seeking talented data engineers to join our rapidly growing team, which includes senior software and data engineers. Together, we drive our data platform from acquisition and processing to enrichment, delivering valuable business insights. Join us in designing and maintaining robust data pipelines, making an impact in our collaborative and innovative workplace.

Responsibilities
Design, implement, and optimize scalable data pipelines for efficient processing and analysis.
Build and maintain robust data acquisition systems to collect, process, and store data from diverse sources.
Take part in developing agentic capabilities.
Mentor, support, and guide junior team members, sharing expertise and fostering their professional development.
Collaborate with DevOps, Data Science, and Product teams to understand needs and deliver tailored data solutions.
Monitor data pipelines and production environments proactively to detect and resolve issues promptly.
Apply and be responsible for best practices in data security, integrity, and performance across all systems.

As we continue to expand and evolve, were looking for a Data Engineer to join our growing team and help shape the future of trust and security in the decentralized world.
We have a large amount of varied, exciting, and unique data on our hands, and were already squeezing value out of it for our customersbut theres so much more in there. Your goal will be to help construct the data in ways that enable both our business users and research group to dig deeper. As our very first dedicated data engineer, youll have a huge impactbut youll also need the independence and proactiveness to own it.
What Youll Do:
Design and build complex data pipelines to ingest, process, and transform data from a variety of sources, especially logs and textual inputs.
Collaborate closely with Software Engineering and Product teams to ensure data is accessible and usable.
Develop efficient ETL processes using frameworks such as DBT, Airflow, or their equivalents.
Own and optimize your data environment (e.g., Snowflake), focusing on performance tuning, governance, and reliability.
Build dashboards for various company-wide use cases.
Implement best practices for data management, quality assurance, and security within cloud infrastructures (AWS).
Enable ML and analytics teams by building pipelines that feed feature stores and model training workflows.