Backend Developer (Python / Google Cloud Platform / Airflow)

Position: Backend Developer
Location: Washington, DC Onsite (5 days/week) Pay Rate: $80/hr W2 (no additional benefits)

About the Role

Our client is building a data analytics platform on Google Cloud Platform (Google Cloud Platform) to power in-app workflows and analytics for users. The stack includes Python microservices, Airflow for pipeline orchestration, and a React/Next.js frontend.

This is a hands-on backend engineering role where you ll design scalable services, optimize data pipelines, and collaborate closely with product and frontend teams.

Top Skills Required

• Python (Core Backend Development) Strong, hands-on coding required

• Google Cloud Platform (Google Cloud Platform) Pub/Sub, BigQuery, Cloud Functions

• Data Pipeline Development Airflow or equivalent orchestration tool

• Infrastructure as Code Terraform (preferred)

• Containerization Docker

• Version Control & CI/CD GitHub, GitHub Actions, Cloud Build

What You ll Do

• Design, implement, and maintain backend services and APIs using Python

• Build and optimize data pipelines with Apache Airflow

• Develop and manage Google Cloud Platform resources (Pub/Sub, Cloud Functions, BigQuery, Cloud Storage)

• Collaborate with frontend and product teams to define service contracts

• Maintain code reliability through testing, monitoring, and troubleshooting

• Contribute to code reviews, mentor team members, and improve best practices

Required Experience

• 4+ years of professional Python development

• Hands-on with Airflow DAGs, operators, and scheduling (strong plus)

• Experience with Google Cloud Platform services Compute Engine, Cloud Functions, BigQuery, Pub/Sub, IAM

• Skilled in containerizing apps with Docker and deploying via CI/CD pipelines

• Solid understanding of SQL and relational databases (NoSQL a plus)

• Familiar with RESTful API design and code quality best practices (testing, linting, typing)

Nice-to-Have Skills

• Experience with Terraform or other IaC tools

• Knowledge of Kubernetes or serverless architectures

• Exposure to event-driven systems (Dataflow, Kafka)

• Understanding of security best practices in cloud environments

• Background in data modeling or statistical analysis (NumPy, pandas, SciPy)

• Familiarity with machine learning frameworks (scikit-learn, TensorFlow, PyTorch)

Culture & Benefits

• Mission-driven, progressive, and entrepreneurial environment

• 33 total PTO days (includes holidays) + 2 extra days per year of tenure

• 3 weeks/year WFH flexibility

• Office closed between Christmas and New Year

• Flexible hours: core 10 AM 4 PM (8-hour workday)