Data Engineer

Let’s face it, a company whose mission is human transformation better have some fresh thinking about the employer/employee relationship. We do. We can’t cram it all in here, but you’ll start noticing it from the first interview. Even our candidate experience is different. And when you get an offer from us (and accept it), you get way more than a paycheck.

You get a personal Better Up Coach, a development plan, a trained and coached manager, the most amazing team you’ve ever met (yes, each with their own personal Better Up Coach), and most importantly, work that matters. This makes for a remarkably focused and fulfilling work experience. Frankly, it’s not for everyone. But for people with fire in their belly, it’s a game‑changing, career‑defining, soul‑lifting move.
Join us and we promise you the most intense and fulfilling years of your career, doing life‑changing work in a fun, inventive, soulful culture. If that sounds exciting—and the job description below feels like a fit—we really should start talking.

We are a hybrid company with a focus on in‑person collaboration when necessary. Employees are expected to be available to work from one of our office hubs at least two days per week, or eight days per month. Our US hub locations include:
Austin, TX;
Chicago, IL;
New York City, NY;
San Francisco, CA; and the Washington, DC metro area. If this is a role based in Europe, our Europe hub locations are London, UK and Amsterdam, NL. Please ensure you can realistically commit to this structure before applying.

At Better Up, you will have the opportunity to leverage your expertise, passion, and drive to craft robust, scalable data systems which will directly impact the lives and well‑being of thousands of workers across the world. Better Up is the global leader in virtual professional coaching, combining world‑class coaching with AI technology and behavioral science to deliver personalized behavior change  mission is to help people everywhere live with greater clarity, purpose, and passion and since our founding in 2013, we have pioneered transformation and peak performance for individuals and organizations.

You will be joining a small team responsible for architecting, building, and maintaining the scalable, enterprise‑grade data systems that power our data products and capabilities. You’ll straddle the worlds of Data Ops, MLOps, and Infrastructure, enabling both the next generation of analytics functionality and an AI Platform to fuel our AI‑driven product innovation.

You will work with stakeholders across the business, understanding their data problems and ultimately unlocking data enablement through centralized standardization of tooling and processes, all with enterprise‑grade best practices in mind for security, privacy, and governance. You will deliver high‑quality, systems‑oriented technical solutions which are both fit for today and ready for tomorrow.

• Architect, build, and maintain data systems that are delivering on end‑customer value
• Centralize and standardize data collection, data transformation and analysis, data storage, and data serving approaches and processes
• Support our ML / GenAI teams and functionality with platform capabilities for data delivery, processing, and infrastructure
• Support our reporting and analytics teams in delivering both internal and customer‑facing business insights
• Stay current with emerging technologies and trends in a fast‑evolving technology ecosystem
• Operationally manage our data infrastructure, vendors, tooling, and processes

• 7+ years of experience in data platform engineering, data infrastructure, or related technical roles
• Strong programming background (e.g. Python)
• Operational maturity (e.g. CI/CD systems, Infrastructure as Code, Kubernetes, monitoring, distributed systems, security and privacy best practices, etc.)
• Experience building and maintaining analytics stacks (e.g. Snowflake, dbt, Looker)
• Running GenAI / ML systems in production (e.g. MLOps tooling, vector search, embedding stores, feature engineering at scale, etc.)
• Architecting data systems (e.g. Airflow, Kafka, general system design)