Data Engineer

About Interval

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.

Our platform is built around three outcomes:

• Control: Keep ownership of your data and how models use it.
• Verify: Audit what happened, why it happened, and where results came from.
• Monetize: Create new revenue opportunities through private, permissioned data exchange.

Role Overview

We are seeking a highly skilled Data Engineer to join our team and revolutionize how enterprises secure, analyze, and monetize their data—on their terms. As a Data Engineer at Interval, you’ll work on building and optimizing secure, scalable data pipelines and infrastructure that ensure privacy, compliance, and enable AI-powered business transformation.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines for ingestion, transformation, and delivery of large datasets across diverse industries.
• Implement and ensure data privacy and security best practices, supporting data sovereignty and compliance with regulatory requirements.
• Collaborate closely with AI/ML engineers, Data Scientists, and Platform engineers to enable advanced analytics and AI capabilities while retaining strict data control.
• 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 and solutions.

Qualifications

• 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 (cloud, hybrid, and/or on-premise).
• Strong proficiency with Python, SQL, and modern data engineering toolsets (e.g., Apache Spark, Kafka).
• Solid understanding of data security, privacy frameworks, and regulatory compliance such as GDPR, CCPA, or equivalent.
• Experience with privacy-first, AI-native, or data sovereignty-focused platforms is a plus.
• Familiarity with industry-specific data challenges (CPG, financial services, energy, supply chain, etc.) is advantageous.
• Excellent analytical and communication skills; proactive and detail-oriented.

Why Interval?

• Shape the frontier of AI, blockchain, and enterprise data infrastructure.
• Enjoy meaningful ownership, flexible work, and the autonomy where data, AI, and privacy meet.
• Thrive in a sharp, mission-driven team backed by top-tier technical leadership and investors.