Data Engineering Team Lead

Description

Rekor Systems, Inc. (Rekor.ai) (NASDAQ: REKR) is a trusted global authority on Roadside Intelligence, delivering cutting-edge AI-driven solutions to make transportation safer, smarter, and more efficient. Our platforms integrate data from computer vision, connected vehicles, and third-party providers to generate real-time insights for Public Safety, Urban Mobility, and Traffic Management.

We are looking for a highly motivated and experienced Data Engineering Team Lead to guide a global team responsible for building and maintaining the data infrastructure that powers Rekor’s products. This team collaborates closely with software engineers, data scientists, product managers, analysts, and external partners to deliver scalable, high-quality data solutions that drive business impact.

Key Responsibilities

• Lead a global team of Software engineers, with a core presence in Israel.
• Own the team’s execution, quality, and alignment to data architecture and company-wide engineering standards.
• Work together with product managers to define priorities for each sprint and align engineering efforts to business goals.
• Guide the team’s involvement in cross-functional projects alongside Software, ML, Analytics, and Partner teams.
• Ensure secure, reliable, and efficient access to internal and third-party data sources across all Rekor products.
• Actively participate in roadmap planning, resource allocation, and technical design reviews.
• Provide mentorship, technical guidance, and growth opportunities to team members.
  
  

• 5+ years of hands-on experience in data engineering, with at least 2 years in a team or technical leadership role.
• Strong technical background in building and maintaining production-grade data pipelines using tools like Airflow, Spark, Kafka, or similar.
• Excellent communication skills, with the ability to clearly convey technical ideas to both technical and non-technical stakeholders.
• Strong cross-functional collaboration skills, including working directly with product managers on sprint planning and aligning engineering with business priorities.
• Proven experience working with both structured and unstructured data, including RDBMS and NoSQL solutions.
• Deep understanding of cloud-based data platforms (preferably AWS) and infrastructure as code.
  
  

• Familiarity with ML pipelines, feature stores, and supporting data scientists in production environments.
• Familiarity with Generative AI tools such as Cursor, GitHub Copilot, or similar technologies.
• Strong grasp of data security, reliability, and compliance practices.
• Exposure to real-time or near-real-time data systems in mobility, IoT, or similar domains.