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