Lead Python Developer (Backend)

Were looking for a Senior Python Developer who can design, build, and scale backend systems and APIs that power data-driven sports coaching experiences—real-time performance tracking, personalized coaching plans, and analytics for athletes and coaches. You’ll own critical services end-to-end, drive architectural decisions for high throughput and low latency, mentor engineers, and partner with Product, Data/ML, and Mobile/Web teams to ship reliable features at speed. 

What You’ll Do

• Architect & Build: Design and implement microservices and public/internal REST/GraphQL APIs using Python (e.g., FastAPI, Django/Django REST Framework, Flask) with a focus on performance, reliability, and security. 
• Scale & Optimize: Lead efforts on horizontal scaling, caching strategies (Redis), asynchronous processing (Celery/RQ), and event-driven patterns (Kafka/Kinesis/Pub/Sub) to handle real-time telemetry and streaming data from wearables and in-app sensors. 
• Data Layer Ownership: Model and optimize data in PostgreSQL/MySQL and NoSQL stores (e.g., DynamoDB, MongoDB, Elastic). Plan indexing, partitioning/sharding, connection pooling, and read replicas. 
• Cloud & Infrastructure: Deliver cloud-native services on AWS/GCP/Azure using Docker and Kubernetes, Infrastructure as Code (Terraform/CloudFormation), and CI/CD pipelines (GitHub Actions/GitLab CI/Azure DevOps). 
• Observability & Reliability: Establish metrics, logs, traces (OpenTelemetry, Prometheus, Grafana, ELK), SLOs/SLIs, rate limiting, circuit breakers, feature flags, and blue/green or canary deployments. 
• Security & Compliance: Implement OWASP best practices, secrets management, API auth (OAuth2/OIDC/JWT), data encryption, and privacy controls. Partner with Security for threat modeling and periodic reviews. 
• Collaboration: Work closely with mobile/web, data engineering, and ML to integrate recommendation engines, computer vision, or coach dashboards. Translate product requirements into robust technical designs and delivery plans. 
• Mentorship & Standards: Raise the bar on code quality, testing (unit/integration/e2e), code reviews, technical docs, and mentoring mid/junior engineers. 
• Technical Leadership: Lead design reviews, drive RFCs, and guide the evolution of our platform architecture. 

Minimum Qualifications

• 10+ years of professional software development, with 8+ years in Python building production backend services. 
• Expert in at least one Python web framework (FastAPI, Django/DRF, Flask) and API design (REST and/or GraphQL). 
• Strong command of asynchronous Python (asyncio), concurrency patterns, and performance profiling (e.g., cProfile, py-spy, uvloop). 
• Solid experience with relational databases (PostgreSQL/MySQL), SQL optimization, and at least one NoSQL technology. 
• Hands-on with message brokers/streaming (e.g., Kafka, RabbitMQ, Kinesis, Pub/Sub) and task queues (Celery/RQ). 
• Proven delivery on cloud platforms (AWS/GCP/Azure), containers (Docker), and orchestration (Kubernetes). 
• Strong experience with CI/CD, automated testing, and monitoring/alerting stacks. 
• Understanding of secure coding, authentication/authorization, and API hardening. 
• Excellent collaboration, communication, and architectural documentation skills. 

Nice to Have

• Experience in sports tech, fitness, or real-time telemetry (BLE/WebSockets/Socket.IO/HTTP/2, gRPC) and time-series data (TimescaleDB/InfluxDB). 
• Exposure to ML pipelines (feature stores, model serving via FastAPI, SageMaker, Vertex AI), or computer vision for form/technique analysis. 
• Knowledge of domain-driven design (DDD), CQRS, event sourcing, and data mesh patterns. 
• Familiarity with GraphQL (Apollo/Federation), API gateways, and edge caching/CDN (CloudFront/Fastly). 
• Experience with payments, subscriptions, and entitlement systems. 
• Contributions to open source, technical blogging, conference talks, or mentorship programs. 

Core Tech Stack (typical)

• Language: Python 3.10+ (type hints, pydantic, asyncio) 
• Frameworks: FastAPI, Django/DRF, Flask 
• Data: PostgreSQL, Redis, DynamoDB/MongoDB, TimescaleDB/Elastic (as applicable) 
• Messaging/Async: Kafka/RabbitMQ, Celery/RQ 
• Cloud/Infra: AWS (EKS, ECS, Lambda, API Gateway, RDS, DynamoDB, S3, CloudWatch) or GCP/Azure equivalents 
• CI/CD & IaC: GitHub Actions/GitLab CI/Azure DevOps; Terraform/CloudFormation 
• Observability: OpenTelemetry, Prometheus, Grafana, ELK/EFK, Sentry 
• Security: OAuth2/OIDC/JWT, Secrets Manager/HashiCorp Vault