Analytics Engineer, DTC E-commerce

About Hyprwork Hyprwork is a fast-growing operator of direct-to-consumer brands in health and wellness. Our flagship brand, Rejuvacare, serves over 400,000 customers who trust us with their health and their money. Through products like RejuvaKnee, we help adults reclaim mobility and live with less pain. We ship primarily to the United States, run a RejuvaCare+ membership program that powers recurring revenue, and acquire customers through paid digital channels. The company has scaled 12x in a single year to nearly 150 people across 15 or more countries. We are remote-first, async-first, and we hold a high standard of accountability across everything we do. The Role This is the first dedicated hire in our data function. Today, data work is spread across developers, marketing, and operations, with no single owner and no shared source of truth. Decisions get made on fragmented reports and manual spreadsheets. We are bringing in one person to change that. We are looking for an Analytics Engineer who does two things at once: builds the data layer and understands what the numbers mean for the business. You will write the SQL, build the models, and set up the reporting. You will also be the person who notices when a metric is telling a story the business needs to act on, and who knows where to dig next to understand why. This is a hands-on, individual-contributor role. It is not a management role, and it is intentionally operational: we need someone who builds, not someone who only directs. Because the function does not exist yet in a structured way, the growth potential is significant. You will define how data works here from the ground up: the models, the metrics, the standards, and the way the rest of the company consumes them. The data itself lives across many places today, from checkout and subscription data, to paid acquisition data, to customer support data in Richpanel and phone data in Aircall, to supply chain and inventory. There is no ERP. Bringing order to that, and turning it into something the business can act on, is the core of the job. The upper end of this role, in scope and in seniority, is for someone who can go beyond reporting and build AI-based solutions for ad performance optimization. Our growth runs on paid acquisition, so a candidate who can apply AI and automation across creative production, media buying, data analysis, and data visualization is exceptionally valuable here. This is not a hard requirement for every applicant, but it is the profile that unlocks the most senior version of this role. What You Will Own Data modeling and transformation: building and maintaining the transformation layer that turns raw, scattered data into clean, reliable models. Using dbt to solve complex modeling problems with a focus on performance, robustness, and scalability. Applying solid ETL and data warehousing concepts. Establishing best practices from scratch: naming conventions, data modeling standards, and data quality testing. Data quality, investigation, and reliability: identifying, investigating, and solving data issues across quality, discrepancies, and missing data. Debugging SQL and tracing problems to their root cause. Building prevention and alerting solutions so issues surface internally before stakeholders ever see a wrong number. Reporting, dashboards, and delivery: building reporting and analytics solutions, including dashboards in Looker, and ensuring accurate and timely delivery of data. Defining the core metrics the business runs on so everyone reads the same numbers. Supporting other contributors as the function grows. Business insight and decision support: understanding, tackling, and communicating problems from both a technical and a business perspective. Staying alert to what the data means for the business, not just whether the pipeline ran. Knowing where to investigate further to understand what to action, and translating findings into clear recommendations for non-technical stakeholders across marketing, operations, and leadership. Ownership: taking ownership of tasks and initiatives end to end, documenting the system so it is maintainable by the team, and communicating with cross-functional teams in a clear, structured, async-first manner.