Senior Analytics Engineer at Scenthound Franchising

United States

<div class="trix-content"> <div><strong>Sr. Analytics Engineer </strong></div><div><strong> </strong></div><div><strong>Company Overview</strong></div><div>Scenthound is the first membership-based franchise providing affordable and accessible wellness-focused dog care, committed to providing every dog with the care necessary to help maintain their health and keep them clean and happy. Franchising since 2019 and on pace to have over 200 locations open by the end of 2026, Scenthound is establishing itself as the preeminent solution for routine and preventive dog care. </div><div> </div><div>Our values…</div><div>·       <strong>Dog First</strong>. We advocate for the health and well-being of every dog in our care.</div><div>·       <strong>One Pack</strong>. We are one company, one team, with one mission. </div><div>·       <strong>Bring Love</strong>. We bring good energy to our work and do our jobs with loving intention.</div><div>·       <strong>Seek Growth</strong>. We believe. We learn. We grow.</div><div>·       <strong>Make a Difference</strong>. We work with purpose. We are driven by a desire to make a positive impact.</div><div> </div><div>We’re looking for a Senior Analytics Engineer who has built and owned production‑grade data models. You’ll work closely with Marketing, Product, Finance, and Operations to turn messy operational data into reliable, well‑modeled, business‑ready datasets.</div><div> </div><div>This role is ideal for someone who enjoys designing dimensional models, improving data reliability, and partnering with business teams to define metrics and attributes that matter.</div><div><strong> </strong></div><div><strong>Success looks like:</strong></div><ul> <li>A stable, governed, high‑trust data environment powering business decisions.</li> <li>Gold‑layer models that business functions rely on daily.</li> <li>Faster delivery of insights, segmentation, and marketing triggers.</li> <li>Reduced data quality issues and improved reliability across pipelines.</li> <li>Clear documentation, lineage, and standards adopted across the data team.</li> <li>Strong cross‑functional alignment and increased data maturity across the organization</li> </ul><div> </div><div><strong>Job Focus: </strong></div><ul> <li>Own the creation and maintenance of enterprise data models used across multiple business functions.</li> <li>Design and implement ETL/ELT pipelines that move, transform, and enrich data across our stack, ensuring data integrity and consistently.</li> <li>Build transformations following clear modeling standards. </li> <li>Improve data reliability through testing, documentation, and thoughtful design.</li> <li>Support activation workflows by delivering trustworthy attributes to downstream tools.</li> <li>Contribute to modeling conventions, review processes, and long‑term data strategy.</li> <li>Maintain a predictable warehouse environment through thoughtful performance tuning and cost management.</li> <li>Partner with business teams to define metrics, segmentation logic, and lifecycle attributes.</li> <li>Collaborate closely with application engineers, analysts, and ML/AI stakeholders to understand their data needs and deliver purpose-built solutions that serve each use case effectively without comprising others.</li> </ul><div><strong> </strong></div><div><strong>Requirements:</strong></div><ul> <li>Proven experience in a cloud warehouse environment and an understanding of how to keep it fast and predictable for costs and performance.</li> <li>Hands-on experience with relational databases, encompassing schema design, query optimization, indexing, and administration.</li> <li>Ownership of production data models that other teams rely on.</li> <li>Have built transformations using a version‑controlled workflow.</li> <li>Have a deep understanding of dimensional modeling with a strong point of view/rationale on <em>why</em> you modeled something a certain way.</li> <li>Experience building and maintaining ETL/ELT pipelines.</li> <li>Experience improving data quality through tests, documentation, and thoughtful design.</li> <li>Familiarity with data governance frameworks, role-based access controls, and PII/data privacy best practices.</li> <li>Familiarity with BI tools from a data model & provisioning perspective. </li> <li>Experience with identity stitching, consent logic, or historical tracking.</li> <li>Have partnered with business teams to define metrics or attributes.</li> <li>Experience supporting customer or lifecycle analytics.</li> <li>Experience delivering attributes or segments to downstream tools.</li> <li>6+ years of professional experience in an analytics engineering role, with at least 2 years in a senior capacity.</li> <li>Experience working in a franchise, multi-location retail, or consumer services business where data spans many operational units is a bonus.</li> <li>You do not need to list every tool you’ve used. We are not looking for a laundry list of tools. We care more about how you think than what tools facilitate outcomes.</li> <li>This role requires collaboration during U.S. business hours.</li> </ul><div> </div><div><strong>Compensation and Benefits</strong></div><ul> <li>Compensation commensurate with experience</li> <li>Health/Dental/Vision insurance </li> <li>Paid time off</li> <li>Company Paid Life and AD&D Insurance</li> <li>Short Term Disability </li> <li>401k with company match</li> <li>Free Scenthound membership for your dog — because of course</li> </ul><div><strong>How to Apply</strong></div><div>To help us identify real practitioners, please include a brief note (no more than 3–5 sentences) describing one mistake you have made in a past data model and what you learned from it. </div><div> </div><div>Applications without this note will not be reviewed.</div><div> </div><div> </div><div> </div><div> </div><div> </div> </div> <p>This is a remote position.</p>