Search the 7 jobs at Pattern Data

The Director of Client Success will oversee customer strategies to enhance satisfaction and growth, lead the Client Success team, ensure effective onboarding and user training, and collaborate with various internal teams. Key responsibilities include developing client relationships, defining key performance metrics, and implementing best practices for exceptional client experiences.

As a Software Engineer I, you will work closely with Senior Engineers and the CTO to design, develop, and maintain document processing systems. You will develop front-end components in React and TypeScript while supporting back-end development in Scala. A key part of the role is building scalable solutions and writing maintainable code.

The Client Experience Manager will enhance client relations by analyzing data to provide insights that drive product adoption and performance at Pattern. Responsibilities include improving business processes, configuring the platform, and communicating effectively with law firm clients.

The Implementation Manager will lead the integration of the Pattern Data platform for mass tort litigations, ensuring accurate claims processing and coordination with client teams. Responsibilities include managing end-to-end project implementations, performing QA testing, and developing standardized processes to enhance efficiency.

The Director of Accounting & Finance will oversee all accounting operations, financial reporting, regulatory compliance, audit coordination, tax planning, cash flow management, and budgeting at Pattern Data. This role requires improving accounting processes and team development while ensuring compliance with accounting standards.

As a Staff Software Engineer, you will architect and implement backend services, primarily in Scala, collaborating with product and executive teams. You'll enhance the platform's architecture and ensure coding standards are met, while delivering solutions that meet business needs.

The Senior Data Engineer will design, maintain, and enhance the company's data analytics pipeline, focusing on data warehouse and ETL processes. Responsibilities include developing tools for monitoring data health, collaborating with stakeholders, and ensuring data accuracy and reliability.