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
- 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
Skills Required
- 8+ years of experience in data engineering
- Experience designing and owning data models for complex, high-scale, low-latency production SaaS products
- Deep expertise in relational, dimensional, entity, or graph-based data modeling
- Experience leading large-scale schema redesigns or data migrations in live, multi-tenant environments
- Hands-on experience building and operating production data pipelines using batch and streaming processing
- Experience with tools such as Spark, Kafka, Airflow, Glue, or similar
- Experience with modern data warehouses, lakehouses, and cloud platforms, preferably AWS
- Understanding of data governance, data quality, row-level security, field-level security, and access control
- Experience implementing data quality testing, monitoring, and observability for data pipelines and assets
- Experience designing semantic layers or data models for analytics, BI, AI, or LLM-based applications
- Ability to drive architecture decisions across teams and write clear design documents
- Experience scoping and planning multi-quarter initiatives
- Strong communication and collaboration skills with product managers, engineers, data scientists, and customer-facing teams
- Familiarity with contract lifecycle management, legal technology, or document-heavy enterprise domains
What We Do
Agiloft is the global value leader in data-first contract lifecycle management (CLM), offering the industry’s only no-code platform with AI on the Inside™ to enhance efficiency, cut review times by up to 80%, and accelerate business. Its Data-first Agreement Platform (DAP) transforms contracts into strategic, data-rich assets, integrating with 1,000+ systems to drive decisions and efficiency. Trusted by brands like Alkermes, Balluff, and TaylorMade, Agiloft boasts a 96% renewal rate and 100% satisfaction for implementations. Backed by KKR, JMI Equity, and FTV Capital, Agiloft empowers businesses to drive smarter strategies, faster decision-making and game-changing competitive advantage. Learn more at www.agiloft.com. We're hiring! To view our current job openings, please visit https://www.agiloft.com/jobs.htm.
Why Work With Us
We are a passionate group of humans dedicated to helping other humans thrive. We may work with contracts, but with careers at Agiloft, the most important contract we keep is the human contract, the commitment we have to each other.
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