We’ve invested heavily in building a modern data and analytics ecosystem—Lift Legacy (1.0/2.0), Airflow-powered ETL pipelines, a BigQuery data warehouse, internal tools like Walk the Store, Lift AI, and multi-tenant client reporting through Looker Studio Pro.
All of these systems depend on a single backbone: the underlying pipelines, marketplace APIs, legacy data flows, and reporting layers that power our client experience. Today, that backbone is primarily owned by one person. We’re now bringing in a dedicated full-stack engineer to scale, harden, and expand the platform.
This role is not speculative—it directly supports strategic initiatives the company has already committed to, with clear ROI through vendor spend reduction, faster delivery, and reduced key-person risk.
Role Overview:
We’re searching for a Full-Stack Developer who can work across our data platform, ETL pipelines, marketplace APIs, and client-facing applications. You’ll collaborate closely with engineering leadership, product, Lift AI, and analytics teams to strengthen our core platform and build the next generation of tools for brands selling on Amazon, Walmart, and other marketplaces.
This is a full-stack role in the sense that you’ll own the data, integration, and business logic layers first, and also contribute to the web/UX layer where needed. It is not a pure front-end or pixel-perfect web design role.
You will play a pivotal role in bringing our most important data capabilities in-house, supporting Walk the Store as it scales, and making our analytics surface truly self-serve for clients.
Job Responsibilities:
1. Data Platform & Airflow ETL
- Harden and standardize Airflow pipelines for reliability, observability, and error handling.
- Break complex DAGs into typed, modular components.
- Ensure clean and timely data delivery across Marketplace, Lift AI, and client reporting.
2. Marketplace API Ownership (Amazon → Walmart)
- Build robust SP-API and Walmart integrations (read + future write actions).
- Move critical data flows away from third-party providers (Cajari, Intentwise).
- Expand our internal dataset coverage over time.
3. Walk the Store – Productization & Scale
- Own backend integrations and data plumbing supporting the product.
- Build features like daily alerts, resolution workflows, and cost-to-fix models.
- Work closely with product and stakeholders to drive WtS to true product-market fit.
4. Client-Facing Analytics (Looker Studio Pro)
- Strengthen and extend our multi-tenant reporting setup.
- Build repeatable patterns for client-specific dashboards and secure data access.
- Increase client stickiness by making analytics a first-class product.
5. Legacy Lift (1.0/2.0) Support & Migration
- Maintain mission-critical features still in daily use.
- Gradually refactor high-value components into modern Python/ETL services.
- Reduce long-term technical debt and central points of failure.
6. Reliability, Monitoring & Disaster Recovery
- Implement backup routines, alerting, and missing-data detection.
- Reduce the “bus factor of 1” currently present in several critical systems.
- Strengthen platform health as we scale.
What Success Looks Like (First 6–12 Months):
- Airflow pipelines are hardened, logged, and standardized.
- High-value datasets previously sourced from vendors are now flowing through in-house APIs.
- Walk the Store features ship faster and with richer data
- Looker Pro reporting becomes a scalable, repeatable onboarding process.
- Platform monitoring catches failures early and reduces surprises.
- Critical Lift Legacy components remain stable while gradually migrating forward.
Job Requirements and Key Competencies:
- Strong experience in Python, ETL, and API integrations
- Airflow or other workflow orchestration experience
- Comfort with SQL and data warehousing (BigQuery preferred)
- Experience building backend services + light front-end (React or similar)
- Ability to structure reliable pipelines and own them end-to-end
- Strong debugging, logging, and monitoring instincts
- Comfortable reading and making targeted changes in an existing PHP/Laravel codebase (even if Python is your primary language)
Soft Skill:
- Ownership mindset
- Clear communication
- Ability to work cross-functionally (data, product, engineering, analytics)
- A bias for practical solutions over theoretical perfection
Reporting Structure:
You will report to the Data Platform Lead and collaborate closely with:
- Lift AI engineering
- Walk the Store product owner
- Analytics & Reporting team
- DevOps, product, and leadership stakeholders
Apply Now
If you’re excited to build a scalable data ecosystem, work across APIs and analytics, and help shape a fast-growing platform used by major brands—this role is for you.