Established in 2021, Independence Pet Holdings is a corporate holding company that manages a diverse and broad portfolio of modern pet health brands and services, including insurance, pet education, lost recovery services, and more throughout North America. We believe pet insurance is more than a financial product and build solutions to simplify the pet parenting journey and help improve the well-being of pets. As a leading authority in the pet category, we operate with a full stack of resources, capital, and services to support pet parents. Our multi-brand and omni-channel approach include our own insurance carrier, insurance brands and partner brands. Clarus is a pioneering pet health technology company on a mission to transform the future of pet healthcare. We are dynamic entrepreneurs improving pet health by providing trusted and transparent information across the entire pet health landscape. Join us in shaping a smarter, healthier future for pets everywhere. As we expand, we are looking for a seasoned Data Architect , in the data team, who can hit the ground running by building data models across the operational and analytics data store. This role will be reporting to the Senior Director of Data and Analytics. Role Overview This is a hands-on role for an experienced Data Architect with a proven track record of implementing a scalable data lake/medallion architecture and building robust data models in partnership with our product and engineering teams. The role is focused on designing and implementing scalable data solutions using Azure Databricks, acting as a subject matter expert in the platform to create efficient data pipelines, manage data lakes, and ensure data quality while leveraging the full capabilities of the Azure cloud ecosystem. Key Responsibilities: Design and implement data architecture solutions using Databricks, Spark, and Azure data services. Develop and optimize data models for both operational and analytical systems. Ensure data integrity, security, and accessibility across various platforms. Integrate data pipelines with event-based and microservice architectures leveraging Service Bus, Event Hub, and Functions. Create and maintain data standards, guidelines, and best practices. Conduct data quality assessments and implement data governance policies. Provide guidance on data storage solutions and ELT/ETL processes. Collaborate with developers, analysts, and data scientists to deliver trusted datasets for reporting, analytics, and machine learning use cases. Participate in architecture discussions, backlog refinement, estimation, and sprint planning. Contribute to defining and maintaining best practices, coding standards, and quality guidelines for data engineering. Perform code reviews, provide technical mentorship, and foster knowledge sharing within the team. Continuously evaluate and enhance data engineering tools, frameworks, and processes in the Azure environment. Qualifications: Company paid short-term and long-term disability 12 weeks of 100% paid Parental Leave Health Savings Account (HSA) Flexible Spending Accounts (FSA) Retirement savings plan Personal Paid Time Off Paid holidays and company-wide Wellness Day off Paid time off to volunteer at nonprofit organizations Pet friendly office environment Commuter Benefits Group Pet Insurance On the job training and skills development Employee Assistance Program (EAP)

• Define the future of AI + human healthcare with innovative data engineering solutions • Architect data platforms in a fast-paced, high-growth environment • Collaborate with teams on multi-stakeholder projects working extensively with healthcare data and standards (e.g. HL7 FHIR, CDS, ICD-10)

• Participate in all aspects of the software and data product development lifecycle from user story generation, through design, development, automated testing and operational support • Improve quality by actively participating in code-reviews and adhering to team quality standards • Work alongside other engineers on the team to elevate technology and consistently apply best practices • Own the execution of medium-to-large sized features with higher-level technical support • Describe and document the details of your work fluidly and accurately for technical peers and non-technical stakeholders • Think holistically about the application and build with an eye towards long term maintainability and efficiency • Collaboratively provide estimates and other input to the client, project managers designers, or others about features to help determine their feasibility, complexity, cost, and priority level • Contribute to a culture of positivity, curiosity, and respect for all individuals

• Provide leadership and guidance to the data engineering team, including mentoring, coaching, and fostering a collaborative work environment. • Set clear goals, assign tasks, and manage resources to ensure successful project delivery. • Work closely with developers to support them and improve data engineering processes. • Support team members with troubleshooting and resolving complex technical issues and challenges. • Provide technical expertise and direction in data engineering, guiding the team in selecting appropriate tools, technologies, and methodologies. • Stay updated with the latest advancements in data engineering and ensure the team follows best practices and industry standards. • Collaborate with stakeholders to understand project requirements, define scope, and create project plans. • Support project managers to ensure that projects are executed effectively, meeting timelines, budgets, and quality standards. • Monitor progress, identify risks, and implement mitigation strategies. • Act as a trusted advisor for the customer. • Oversee the design and architecture of data solutions, collaborating with data architects and other stakeholders. • Ensure data solutions are scalable, efficient, and aligned with business requirements. • Provide guidance in areas such as data modeling, database design, and data integration. • Align coding standards, conduct code reviews to ensure proper code quality level. • Identify and introduce quality assurance processes for data pipelines and workflows. • Optimize data processing and storage for performance, efficiency and cost savings. • Evaluate and implement new technologies to improve data engineering processes on various aspects (CICD, Quality Assurance, Coding standards). • Act as main point of contact to other teams/contributors engaged in the project. • Maintain technical documentation of the project, control validity and perform regular reviews of it. • Ensure compliance with security standards and regulations.