Data Engineer

About Interval
Interval empowers businesses to unlock their private data’s potential, turning it into intelligent, actionable insights—while retaining full sovereignty and privacy. Our AI-native platform is designed for security, data sovereignty, monetization, and intelligent orchestration. We serve industries such as CPG, construction, financial services, energy, transportation, and supply chain, transforming how businesses analyze and leverage their data.

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?
- Impact: Shape a platform that enables enterprises to control, secure, and monetize their most valuable asset—data.
- Innovation: Work at the intersection of AI, privacy, and data infrastructure.
- Growth: Collaborate with a dynamic team revolutionizing data use across multiple industries.