Original listing text, shown exactly as published by the company.
Key Responsibilities
Growth Infrastructure & Systems
- Design, implement, and maintain scalable infrastructure that supports growth and experimentation needs.
- Build and optimize analytics pipelines to capture key product and growth metrics (acquisition, activation, retention, etc.).
- Develop automated workflows for user onboarding, campaign delivery, and performance tracking.
Experimentation & Optimization
- Support A/B testing frameworks and integrate them into production systems.
- Enable reliable data collection and evaluation for growth experiments.
- Automate deployment and rollout of growth feature flags and tests.
Cross-Functional Collaboration
- Partner with Growth Product Managers, Data Engineers, and Analysts to define technical requirements for growth initiatives.
- Translate business goals into technical specifications and system designs.
- Provide guidance on performance, reliability, and scalability trade-offs.
Monitoring & Reliability
- Implement monitoring and alerting for growth infrastructure services.
- Troubleshoot production issues and optimize for uptime and performance.
- Ensure data quality and consistency for reporting and decision-making.
Continuous Improvement
- Evaluate new tools, frameworks, and platforms that accelerate growth engineering.
- Drive best practices in infrastructure as code, CI/CD, and automated testing.
- Train and mentor teammates on growth infrastructure principles. (Teal)
Required Qualifications
- Bachelor’s degree in Computer Science, Software Engineering, or related technical field.
- 3+ years of experience building backend or infrastructure-focused services.
- Strong programming skills in languages such as Python, Go, or JavaScript.
- Experience with cloud platform infrastructure (e.g., AWS, GCP, Azure).
- Solid understanding of data pipelines, ETL processes, and databases.
- Experience with CI/CD systems and Infrastructure as Code (Terraform, CloudFormation, etc.).
- Experience with experimentation platforms (StatSig, Segment, LaunchDarkly, or in-house).
Nice to Have
- Familiarity with growth metrics and product analytics tools (Amplitude, etc.).
- Experience designing and scaling A/B testing systems and feature flag orchestration.
- Proficient with containerization (Docker, Kubernetes) and distributed systems.
- Knowledge of observability tools (Datadog, etc).
What Success Looks Like
- Growth initiatives that deploy reliably and quickly with minimal manual intervention.
- High-fidelity data pipelines that enable real-time insight into key growth metrics.
- Growth teams are empowered to run experiments and launch campaigns without heavy infrastructure support.
