Data Platform Engineer

About the Company

Beatdapp is a venture-backed startup delivering the most advanced streaming integrity and recommendation technology in the world. We leverage our "Trust & Safety Operating System" to power a new generation of discovery by building recommendation engines on a foundation of clean, authentic data.

Responsibilities

• Design, build, and maintain scalable data pipelines and processing workflows for high-volume streaming data
• Manage and optimize multi-cluster Kubernetes (K8s) environments and implement autoscaling policies
• Orchestrate live service deployments using A/B testing and Canary release strategies
• Design and maintain infrastructure using Infrastructure as Code (IaC) principles
• Own end-to-end observability including logging, tracing, and metrics across backend services
• Partner with security teams to enforce patch management, secrets handling, and data encryption
• Automate routine operational tasks and manage system uptime and outages

Requirements

• 3+ years of professional experience in Backend, DevOps, or Data Engineering
• Deep familiarity with Kubernetes (K8s), including compute, networking, and scaling
• Proficiency in writing production-grade backend services and data processing code in Python
• Proven track record with CI/CD pipelines and container management (Docker/Podman)
• Strong understanding of relational, non-relational, and columnar datastores
• Experience with distributed data systems and secure cloud networking

Preferred Qualifications

• Hands-on experience with Google Cloud Platform (GCP)
• Experience with Terraform
• Hands-on work with Service Mesh (Istio or Linkerd)
• Experience with data orchestration tools like Airflow, vector databases, or feature stores
• Experience with GitHub Actions (GHA)
• Ability to create clear architecture diagrams and technical design documents