Posted at: 4 March
Mid-Level Data Engineer (Temporary)
Company
Workana
Workana is a freelance marketplace platform based in Brazil, operating as a B2B and B2C SaaS provider that connects companies with independent talent across various sectors including IT, design, and marketing.
Job Type
Contract
Allowed Applicant Locations
Worldwide
Job Description
We are looking for a Mid-Level Data Engineer with strong experience in Python and AWS Serverless architectures to support a critical runtime upgrade project.
The main objective is to upgrade multiple production services from Python 3.9 to Python 3.13, modernize the Serverless Framework infrastructure, and decommission legacy services. This work is time-sensitive due to the upcoming AWS Python 3.9 deprecation.
Responsibilities
- Upgrade Python runtime (3.9 → 3.13) across multiple serverless applications.
- Upgrade Serverless Framework (v3 → v4) and update dependencies.
- Maintain and update CI/CD pipelines and deployment workflows.
- Test and deploy services across dev, staging, and production environments.
- Identify and safely decommission deprecated services.
- Document changes and provide knowledge transfer to the internal team.
Technical Environment
Infrastructure
- Serverless Framework
- AWS Lambda
- API Gateway
- Step Functions
- CloudFormation
- CodePipeline / CodeBuild
Application Stack
- Python
- Flask APIs
- Data processing libraries (boto3, pandas, psycopg2)
CI/CD
- Bitbucket Pipelines
- Docker
- 3–5 years experience as a Data Engineer or Backend Engineer
- 3+ years of Python development
- Experience with AWS serverless services (Lambda, API Gateway, Step Functions)
- Hands-on experience with Serverless Framework
- Experience with CI/CD pipelines and automated deployments
- Experience upgrading Python runtimes in production
- Familiarity with Flask-based APIs
Nice to Have
- AWS CDK experience
- Redshift or data warehouse experience
- Python unit testing (pytest / unittest)
- AWS certifications
Engagement Details
- Full-time independent contractor (40 hours/week)
- Duration: 10–12 weeks with potential extension
- Fully Remote work
- Compensation in USD