דרושים » הנדסה » Experienced Data Engineer

We are looking for a brilliant, quick-learner Data Engineer for our data engineering team - an independent logical thinker who understands the importance of data structuring for macro-business decisions.
The position combines high technical skills with business orientation, working closely with the analysts and the R&D team, and affecting the company's cross-departments decisions directly. Our Data Engineer should have the ability to speak in technical and practical terms, and more importantly, lead from one to the other, while dealing with challenges and creating them - to make our team even better than it is.
Roles and Responsibilities:
Creating and structuring end-to-end data pipelines & ETLs: from the source all the way to the analysts hands, enabling them the ideal conditions to make smart and data driven business decisions.
Cracking top industry data challenges while initiating and building creative technical solutions - in house Device Graph, Server-to-Server to multiple systems, Privacy challenges, Online-to-Offline and more.
Deep understanding of the business needs, technical requirements and the companys roadmap - and translating it into custom made data solutions and scalable products.
Craft code following best practices to ensure efficiency, while integrating CI/CD principles.
Writing multi-step scalable processes from more than 50 data sources - Marketing. Operations, CS, Product, CRM and more... tying them up to a valuable & useful source of insights for the analysts.
Understanding data challenges and weaknesses, and managing high standards monitoring and reliability processes.

Lead the design, implementation, and ongoing management of our company's data pipeline architecture.
Lead team architectural discussions
Manage a team of 2-3 data engineers
Work as an integral part of the data team and work closely with data Scientists, data Analysts and data Engineers.
Work directly with others (Developers, Product, and Internal stakeholders) to develop a solid understanding of the business application and requirements for which the application is being designed.

We are looking for a Data Engineer.
Main responsibilities:
Provide the direction of our data architecture. Determine the right tools for the right jobs. We collaborate on the requirements and then you call the shots on what gets built.
Manage end-to-end execution of high-performance, large-scale data-driven projects, including design, implementation, and ongoing maintenance.
Monitor and optimize our (teams) cloud costs.
Design and construct monitoring tools to ensure the efficiency and reliability of data processes.

Design, build, and launch data infrastructures that support multiple use cases across different products or domains.
Collaborate with engineers, product managers, data scientists, and other stakeholders to understand data needs.
Solve challenging data integration problems, utilizing optimal ETL patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
Lead end-to-end data projects from infrastructure design to production monitoring and visualization.

Our Research team is growing, and we are looking for a Senior Data Engineer to join the team.
Not Your Typical Senior Data Engineer Role
You're a crucial pivot in our R&D unit, ensuring our data flows seamlessly, is stored efficiently, and can be accessed and interpreted for justice at scale. You will be responsible for designing our data architecture, implementing and maintaining data pipelines from various sources, and building our databases.
There is no one way of doing things. We are open to new ideas and we encourage creativity, new initiatives and entrepreneurial minds.
Responsibilities:
You will devise scalable solutions to enhance the capabilities of our legal data team to analyze factual information and extract legal implications from it.
Design data analytics modeling solutions with the data science and ML engineers
Collaborate with peer engineering teams (backend & frontend developers and architects) as well as data scientists, product managers, and data analysts to understand business priorities and translate these requirements into data models.
Work with DevOps and engineers to design and implement our infrastructure.