Senior Python/AWS/Backend Engineer - Remote (ONLY W2) — United States

Job Title: Senior Python Backend Engineer

Location: Remote

Contract: 12 months may extend

PR: $58/hr W2

Role Overview:

Location: Remote / Onsite (Candidate should be willing to visit onsite if required)

Job Summary:

Looking for a highly technical Senior Software Engineer with strong Python, AWS, and backend development experience to design, build, deploy, and support production-grade data products and cloud-based solutions for precision agriculture.

Key Responsibilities

• Develop Python-based REST APIs, backend services, AWS Lambda functions, and data-processing applications.

• Design and maintain AWS cloud infrastructure using services like Lambda, API Gateway, S3, SQS, EventBridge, IAM, and RDS/Aurora.

• Build and manage data pipelines for ingestion, transformation, and processing.

• Work with PostgreSQL/Aurora databases, including schema design, migrations, and performance optimization.

• Implement Infrastructure as Code using Terraform.

• Develop CI/CD pipelines using GitHub Actions, automated testing, and deployment practices.

• Integrate Databricks and support data-processing workflows.

• Monitor and troubleshoot production applications using Datadog.

• Improve application scalability, reliability, security, performance, and cloud cost efficiency.

Must-Have Skills

1. Strong Python development experience with production deployment.

2. REST API and backend services development.

3. Strong AWS experience – Lambda, API Gateway, IAM, S3, SQS, EventBridge, RDS/Aurora.

4. PostgreSQL / Relational databases.

5. Terraform / Infrastructure as Code (IaC).

6. CI/CD, Git, GitHub, and automated testing.

7. Production troubleshooting and problem-solving skills.

Good-to-Have Skills

• Databricks, Spark, PySpark, SQL, Delta Lake.

• Event-driven and serverless architecture.

• Docker and containerization.

• DBMate, Pydantic, AWS Lambda Powertools.

• OAuth/OIDC authentication.

• Datadog monitoring and observability.

• GitHub Actions.

• Experience with high-volume machine, agricultural, geospatial, or logistics data.