Data Engineer

At our company, we are revolutionizing the insurance industry with the world's first Marketing OS - a comprehensive solution tailored to the unique marketing and distribution needs of insurance organizations.
Our intelligent solutions combine the power of AI, machine learning, and real-time data to reshape marketing strategies and drive profitable growth for top insurers.
Founded in 2015 and headquartered in Israel, our partners with leading US insurance companies, helping them uncover hidden growth opportunities and optimize their marketing budgets with unparalleled precision and efficiency.
We are looking for a Skilled Data Engineer who is passionate about handling data infrastructure, pipelines, and systems with strong problem-solving abilities while collaborating with multiple teams and playing a key role in their core team.
Responsibilities
Establishing robust and scalable data pipelines for acquiring, processing, and storing large volumes of data- from the Design stage, construction, install, test, and maintenance
Designing a scalable and flexible architecture that can grow with the company, supporting various use cases, therefore involves working closely with data analysts and stakeholders to understand requirements and design appropriate solutions.
Build and manage data warehouses and data lakes for storage and analysis of large dataset-choosing appropriate technologies, setting up storage solutions, and ensuring data accessibility and security.
Integrate various data sources (both structured and unstructured) into a unified data platform. This involves leveraging technologies like ETL (Extract, Transform, Load) processes or real-time streaming platforms
Design and implement data models, schemas, and database structures optimized for performance, scalability, and reliability. Knowledge of SQL and NoSQL databases is essential.
Develop and implement data quality processes to ensure accuracy, completeness, and consistency of data.
Monitor and optimize data infrastructure performance, identify and resolve bottlenecks, and ensure systems meet data availability and latency SLAs.
Implement security measures to protect sensitive data.
Work closely with cross-functional teams including data analysts and software engineers to understand data requirements and provide technical support
Stay updated with emerging technologies and best practices in data engineering, evaluating and incorporating new tools and techniques to enhance data infrastructure and processes.