Senior Database Engineer at Hoopo Systems Ltd

, , Israel -

Full Time

Start Date

Immediate

Expiry Date

10 Oct, 26

Salary

0.0

Posted On

12 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Azure SQL, Elasticsearch, OpenSearch, T-SQL, Query Optimization, Python, PowerShell, CI/CD Pipelines, Database Indexing, Table Partitioning, NoSQL, Data Security

Industry

technology;Information and Internet

Description

Global supply chains move the world, and most of it is currently invisible. Hoopo is changing that by bringing Fleet Intelligence to the world's largest shipping and transportation operations through a unique combination of hardware, signal processing, and AI. We're looking for an Experienced Database Engineer to join our growing R&D team. In this role, you will work closely with development and research teams to build scalable, high-performance database infrastructure that ingests and processes data from millions of IoT devices operating across maritime, transportation, and aviation environments. You will work across both relational (Azure SQL) and search-oriented (Elasticsearch/OpenSearch) systems. You will develop our data layer on Azure SQL Database, alongside our search/NoSQL infrastructure. About Hoopo Hoopo is a venture-backed startup headquartered in Herzliya, Israel. We digitize unpowered fleets (containers, chassis, trailers, airport ground equipment, and more) - using the world’s most power-efficient tracking devices coupled with signal processing that makes it work in the world's harshest and most challenging environments. On top of that, we are building an AI-powered fleet intelligence platform that turns raw location data into operational insights for some of the largest shipping and logistics companies in the world. * At least 7 years of hands-on experience in database engineering / development. * Experience with large scale databases that have millions of transactions per day. * Strong T-SQL skills, with proven experience writing and tuning stored procedures. * Solid understanding of indexing strategy and query optimization. * Experience with table partitioning and data retention/archival strategies for large or time-series datasets. * Practical experience operating Azure SQL Database and working in the Azure Portal. * Experience defining backup/restore and data-security policies on Azure SQL (point-in-time restore, access control, encryption). * Experience monitoring databases and acting on performance and health metrics. * Hands-on experience with a NoSQL / search engine such as Elasticsearch or OpenSearch. * Experience building and maintaining CI/CD pipelines for databases (schema versioning, automated deployments). * Proficiency in Python and PowerShell for automation and scripting. * Proactive approach - Ability to diagnose and resolve performance problems independently. * Collaborate with developers to design and implement efficient schemas and data-access patterns. * Design, write, and maintain stored procedures, functions, and views in Azure SQL Database. * Analyze and optimize query performance, including partitioning, index design, execution-plan analysis, and resolving bottlenecks. * Implement retention/archival policy according to our customer needs. * Monitor database health, performance and availability - set up alerting, track key metrics, and respond proactively to issues. * Manage and monitor Azure SQL resources through the Azure Portal (provisioning, scaling, performance metrics, security configuration). * Define and implement database backup/restore and security policies. * Build and maintain database CI/CD pipelines - schema migrations, version control, and automated deployments. * Build and maintain search and NoSQL data flows using Elasticsearch or OpenSearch. * Automate database operations and tooling using Python and PowerShell. Experience using AI tools (preferably Claude) for data analysis and rapid development of stored procedures.

Responsibilities

Build and maintain scalable database infrastructure using Azure SQL and search-oriented systems to process IoT data. Responsibilities include optimizing query performance, managing data retention policies, and automating database operations via CI/CD pipelines.