Data Engineer

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interVal

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2019

☁️ SaaS

💳 Fintech

🤖 Artificial Intelligence

💰 $1.2M Seed Round - InterVal on 2021-04

SaaS • Fintech • Artificial Intelligence

interVal is a SaaS platform that uses machine learning and natural language processing to extract, analyze, and surface actionable insights from year-end financial and tax documents. It transforms raw financial statements and integrated bookkeeping data (QuickBooks Online, Xero, Sage, Caseware) into valuation metrics, business health KPIs, protection gaps, loan and investment signals, and client-ready reports to help wealth managers, accounting firms, banks, and other financial institutions identify opportunities and grow AUM. The platform emphasizes enterprise-grade security (SOC 2 Type II, AWS hosting), automated advisory workflows, and features aimed at making advisors more proactive and efficient when serving SMB clients.

📋 Description

• 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.

🎯 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 (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.

🏖️ Benefits

• 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