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’ll collaborate with Product and Engineering to design and deliver a new, more efficient data model that will serve as the foundation for contract intelligence, AI-extracted data, and analytics across our CLM platform. You will play a key role in deciding the go-forward data model and system of record, and in leading its implementation from initial rollout through expanded adoption.
- Job Responsibilities
- Lead the design and delivery of a new, efficient and scalable data model, and plan the transition including migration strategies that minimize disruption for existing customers
Partner with Product and Engineering leadership to define the long-term data architecture and system of record, and drive 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 that powers customer insights, workflow automation, and AI-driven features
Ensure data platforms meet high standards for performance, security, privacy, compliance, and cost efficiency
Implement monitoring and automated data quality checks to keep pipelines and data assets reliable and trustworthy
Establish data governance standards, including documentation, lineage, and retention
Collaborate with Data Science, ML, Professional Services, and customer-facing teams on analytics, integrations, and data migrations
Provide technical guidance and mentorship, lead design and code reviews, and contribute to the data roadmap
Stay current with advancements in data engineering, data modeling, and cloud data platforms to identify and implement best practices
Leveraging AI assisted tools to enhance productivity, streamline workflows, and support day-to-day activities
- Other duties as assigned
- Required Qualifications
- A little bit about you
8+ years of experience in data engineering, with a track record of designing and owning data models for complex, production SaaS products with high scale and low latency
Deep expertise in data modeling, including relational, dimensional, and entity or graph-based approaches, and in choosing the right structure 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 data pipelines, including batch and streaming processing, using tools such as Spark, Kafka, Airflow, Glue, or similar.
Experience with modern data platforms, including warehouses and lakehouses, and with cloud platforms, preferably AWS
Solid understanding of data governance, data quality, and row- and field-level security and access control models with experience implementing data quality testing, monitoring, and observability for data pipelines and data assets.
Experience designing semantic layers or data models that power analytics, BI, and AI or LLM-based applications
Demonstrated ability to drive architecture decisions across teams, write clear design documents, and scope and plan multi-quarter initiatives
Strong communication skills to effectively collaborate with diverse teams, including product managers, engineers, data scientists, and customer-facing teams
Familiarity with contract lifecycle management, legal tech, or document-heavy enterprise domains is a plus
