At manifestlaw.com we are revolutionizing the legal industry as the world's first AI-native law firm. We're on a mission to make legal services faster, better, and accessible to millions by leveraging cutting-edge AI and automation. With $27M in funding from Tier-1 investors and a meteoric rise to $6.5M ARR in just 13 months, we're not just growing - we're reshaping how legal services are delivered.

Our AI-powered platform enables lawyers to be 10x more productive, offering tools like real-time case tracking, automated document generation, and upfront pricing. As we scale toward $38M ARR, we're looking for exceptional talent to join our team and help us build the future of legal tech.

We're seeking a Senior Data Engineer, AI & Analytics to build the data foundation that powers internal reporting, analytics, and AI-driven systems across Manifest. This is a hands-on, high-autonomy role focused on architecture and delivery, not people management. You will build reliable, well-structured, and production-ready data systems, designing pipelines, data models, and access layers that make company data accurate, consistent, and accessible.

What You'll Do

• Build and maintain scalable data pipelines across product, business, partnership, and go-to-market systems.
• Design and improve the company's core warehouse architecture and data models, with BigQuery as a central layer.
• Create a unified and secure data layer that supports internal AI agents, analytics assistants, and automated insight generation.
• Own foundational instrumentation quality, event coverage, and data validation across key workflows to improve trust in core metrics.
• Improve data accessibility so internal users can query trusted company data through dashboards, tools, and natural-language interfaces.
• Implement proactive monitoring systems that detect metric changes, surface anomalies, and trigger alerts.
• Partner with product, operations, marketing, and leadership to translate ambiguous business questions into durable data systems.

What We're Looking For

• 5+ years of experience in data engineering or analytics engineering.
• Strong experience with BigQuery (or similar cloud data warehouses) and building production-grade SQL transformations.
• Experience integrating data from multiple systems such as product databases, CRMs (HubSpot), analytics tools (Amplitude), and event streams.
• Strong understanding of data quality, observability, testing, reconciliation, schema design, and alerting.
• Comfort working on AI-adjacent systems, such as retrieval layers, agent-friendly data access patterns, semantic layers, or internal analytics tooling.
• High autonomy: you can be the primary technical owner for the company's core data layer, working from ambiguous requirements.
• This role does not include people management; it's an individual contributor role with architect-level ownership.

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