Data Engineer

About the Company

Interval helps enterprises turn messy, underused data into governed, high-confidence intelligence—without handing control to a black box. We bring compute to your data with a private data lakehouse, verifiable audit trails, and U-AI, our contextual AI framework for secure AI workflows.

Responsibilities

• Design, develop, and maintain scalable data pipelines for ingestion, transformation, and delivery of large datasets
• Implement and ensure data privacy and security best practices, supporting data sovereignty and compliance
• Collaborate with AI/ML engineers, Data Scientists, and Platform engineers to enable advanced analytics
• Optimize data platforms and systems for performance, reliability, and cost efficiency
• Build tools and frameworks for secure, privacy-preserving data processing and orchestration
• Develop and maintain documentation, data models, and technical workflows
• Partner with cross-functional teams to launch new data-driven product features

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
• Proven experience in designing and building ETL pipelines and data infrastructure
• Strong proficiency with Python and SQL
• Experience with modern data engineering toolsets such as Apache Spark or Kafka
• Solid understanding of data security, privacy frameworks, and regulatory compliance (GDPR, CCPA)

Preferred Qualifications

• Experience with privacy-first, AI-native, or data sovereignty-focused platforms
• Familiarity with industry-specific data challenges in CPG, financial services, energy, or supply chain