Expected responsibilities:

• Designing and building scalable data pipelines (batch + streaming)
• Developing data infrastructure to support analytics and ML workflows
• Building secure, scalable APIs for data and model access
• Implementing event-driven architectures (Kafka) and orchestration (Airflow)
• Supporting Data Science and ML teams with platform capabilities
• Ensuring data observability, governance, and system reliability

We are looking for strong, recent hands-on experience (last 2–3 years) with:
Core stack:

• Kafka (streaming)
• Airflow (orchestration)
• SQL + NoSQL databases
• Cloud platforms (AWS preferred)
• API development

Infrastructure:

• Docker / Kubernetes
• Infrastructure as Code (Terraform / CloudFormation)
• CI/CD pipelines
• Monitoring & observability

Bonus:

• Experience supporting ML pipelines
• Exposure to tools like SageMaker or OpenAI