Saga
11 - 50 employees
Founded 2024
🤖 Artificial Intelligence
☁️ SaaS
🤝 B2B
Artificial Intelligence • SaaS • B2B
<Saga> Saga is a lawyer-centric AI platform and SaaS product that helps law firms and legal teams accelerate review, drafting, and simulation of contracts and legal documents. The platform converts document directories into structured, queryable tables, integrates bi-directionally with Microsoft Word (comments and tracked changes), enables role-based legal simulations, and provides training and adoption services (Saga Amplify) plus ongoing research (Saga Lab). Built on Microsoft Azure with GDPR-compliant, enterprise-grade security and private customer databases, Saga targets legal professionals and firms seeking secure, practical AI tools and workflow integration.
Data Engineer, Analytics – Amplify Platform
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Saga
11 - 50 employees
Founded 2024
🤖 Artificial Intelligence
☁️ SaaS
🤝 B2B
Artificial Intelligence • SaaS • B2B
<Saga> Saga is a lawyer-centric AI platform and SaaS product that helps law firms and legal teams accelerate review, drafting, and simulation of contracts and legal documents. The platform converts document directories into structured, queryable tables, integrates bi-directionally with Microsoft Word (comments and tracked changes), enables role-based legal simulations, and provides training and adoption services (Saga Amplify) plus ongoing research (Saga Lab). Built on Microsoft Azure with GDPR-compliant, enterprise-grade security and private customer databases, Saga targets legal professionals and firms seeking secure, practical AI tools and workflow integration.
📋 Description
• Build and scale data pipelines for product events, usage data, and customer datasets • Develop analytics infrastructure using technologies like Kafka, ClickHouse, and PostgreSQL • Own data models, KPI definitions, and metric layers powering dashboards and product features • Build reliable ingestion processes for both structured and messy customer-provided datasets • Ensure privacy-first data practices through anonymisation, pseudonymisation, and tenant-level controls • Collaborate with engineering and product teams to make data accessible, trusted, and actionable
🎯 Requirements
• 4+ years of experience in data engineering • Strong SQL and Python skills • Experience with analytics databases (ClickHouse preferred) and streaming pipelines (Kafka) • Strong data modelling skills across OLTP and OLAP systems • Experience building KPI/metric layers and working with analytics sources such as PostHog • A strong understanding of privacy engineering and GDPR requirements
🏖️ Benefits
• High ownership and autonomy - you'll own product quality across the platform • Opportunity to shape the user experience of a fast-growing legal innovation company • Collaborative international team that values craftsmanship, thoughtful engineering, and continuous improvement
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