Job Details

Must have skills:

7–10+ years of experience in backend engineering and distributed system development.

Strong proficiency in Python, OOP principles, and modern frameworks such as FastAPI / Django REST Framework.

Deep expertise in building RESTful APIs, microservices, and event-driven architectures.

Hands-on experience with AWS services including Lambda, API Gateway, S3, DynamoDB, CloudWatch, Step Functions,

SNS/SQS, Glue, Athena, and IAM.

Strong knowledge of SQL and NoSQL databases, query optimization, and schema design.

Expertise in ETL / ELT pipeline design, data modeling, and data quality frameworks.

Proficiency with orchestrators such as AWS Step Functions, Airflow, Prefect, or Dagster.

Solid understanding of Docker, containerized development, and microservice deployment patterns.

Experience with infrastructure-as-code, preferably AWS CDK (Python) or Terraform.

Ability to design scalable APIs, data flows, and backend systems with clear architectural reasoning.

Strong analytical and problem-solving skills, with the ability to translate complex requirements into technical implementation.

Experience working in cross-functional teams, collaborating with frontend, data, QA, and product stakeholders.

Roles and Responsibilities:

Lead the design and development of cloud-native backend systems, REST APIs, and scalable data pipelines.

Architect and optimize ETL workflows, ensuring efficient ingestion, transformation, and storage of large datasets.

Own the end-to-end technical delivery, including system design, implementation, integration, code reviews, and performance

 tuning.

Collaborate with system architects and domain experts to define backend and data platform architecture.

Implement and maintain AWS infrastructure using CDK, ensuring security, scalability, and cost efficiency.

Build robust monitoring, logging, and ing for production systems to ensure reliability and traceability.

Work with analytics and product teams to transform business requirements into actionable backend and data solutions.

Optimize data queries, pipelines, and API performance across AWS services.

Ensure best practices in code quality, CI/CD automation, containerization, and documentation.

Solve complex technical problems with strong reasoning, structured thinking, and a data-driven approach.

Mentor junior engineers, conduct design reviews, and contribute to engineering excellence across teams.