Staff Data Engineer - Agiloft

About Agiloft

As a global leader in data-first contract lifecycle management (CLM) software, Agiloft helps organizations manage the end-to-end process of proposing, negotiating, signing, and leveraging contracts using our Data-first Agreement Platform (DAP). With contract data as the foundation, customers collaboratively reach agreements and leverage contract visibility to gain competitive advantage. Recognized as a market leader by Gartner, Forrester, and IDC, Agiloft combines no-code configuration, pragmatic AI, and robust integrations across enterprise contract lifecycles.

Position Overview

We are looking for an experienced Staff Data Engineer to lead the next generation of our contract data model. In this role, you will collaborate with Product and Engineering to design and deliver a new, highly efficient data model that serves as the foundation for contract intelligence, AI-extracted data, and analytics across our CLM platform. You will play a central role in shaping the go-forward data model and system of record, leading its technical implementation from initial rollout through widespread adoption.

Job Responsibilities

• Lead the design and delivery of a new, efficient, and scalable data model, planning transition and migration strategies that minimize disruption for existing customers.
• Partner with Product and Engineering leadership to define long-term data architecture and the system of record, driving key architectural decisions across teams.
• Design, build, and maintain scalable data pipelines and data flows across core applications, AI services, and analytics systems.
• Build and evolve the data warehouse and analytics layer powering customer insights, workflow automation, and AI-driven capabilities.
• Ensure data platforms satisfy stringent requirements for performance, security, privacy, compliance, and cost efficiency.
• Implement monitoring and automated data quality checks to keep data assets and pipelines reliable and observable.
• Establish data governance standards, including documentation, data lineage, and retention policies.
• Collaborate with Data Science, ML, Professional Services, and customer-facing teams on analytics, integrations, and data migrations.
• Provide technical mentorship, lead design and code reviews, and contribute actively to the technical data roadmap.
• Stay current with industry advancements in data engineering, data modeling, and cloud platforms to incorporate best practices.

Required Qualifications

• 8+ years of data engineering experience, with a track record of designing and owning data models for complex, production SaaS products at high scale and low latency.
• Deep expertise in data modeling (relational, dimensional, entity, or graph-based approaches) and selecting optimal structures for scale, flexibility, and performance.
• Proven experience leading large-scale schema redesigns or data migrations in live, multi-tenant environments with minimal customer disruption.
• Hands-on experience building and operating production batch and streaming data pipelines with tools such as Spark, Kafka, Airflow, Glue, or similar.
• Experience with modern cloud data platforms, warehouses/lakehouses, and AWS services.
• Solid understanding of data governance, data quality, and row- and field-level security/access control models, including experience with data testing and observability tooling.
• Experience designing semantic layers or data models powering analytics, BI, and AI/LLM-based applications.
• Demonstrated ability to write clear architecture design documents, lead cross-team technical decisions, and scope multi-quarter initiatives.
• Strong communication and cross-functional collaboration skills.
• Familiarity with contract lifecycle management, legal tech, or document-heavy enterprise domains is a plus.