Job Summary:

We are looking for a highly skilled Senior Software Engineer with strong expertise in Python-based microservices, ETL development on cloud-native infrastructure. This role focuses on building high-performance backend systems designed to handle large-scale telemetry, analytics, and observability data in a distributed environment.

You will be responsible for developing scalable microservices, building robust ETL pipelines, and integrating with cloud-based data systems like AWS S3, Athena, and Elasticsearch. Experience with Kubernetes, FluentD, and large-scale data handling in production environments is key.

This role is ideal for someone with strong backend skills, experience with distributed systems, and a passion for solving real-world performance and integration challenges.

Key Responsibilities:

• Design and implement scalable microservices and REST APIs using Python.
• Design and implement cloud-native microservices and RESTful APIs using Python.
• Build and manage ETL pipelines to ingest, transform, and store large volumes of telemetry and analytics data.
• Develop backend services that scale horizontally and integrate with high-throughput messaging systems.
• Work with Elasticsearch, AWS Athena, S3, and MongoDB for data ingestion, indexing, and querying.
• Containerize services using Docker and manage deployments using Kubernetes (K8s).
• Set up log collection, routing, and monitoring pipelines using FluentD and observability tools.
• Troubleshoot and resolve complex production issues in cloud-native and distributed environments.
• Collaborate with QA, DevOps, and architecture teams for integration, validation, and deployment.
• Participate in system design discussions, architecture reviews, and performance tuning efforts.

Required Skills:

• 6+ years of experience in backend development using Ruby, Python and frameworks like FastAPI or Flask.
• Expertise in designing and deploying cloud-native microservices at scale.
• Strong experience with ETL development, especially for large datasets in distributed environments.
• Hands-on with Kubernetes and Docker environments.
• Deep knowledge of AWS services (e.g., Athena, S3, EC2, Lambda, CloudWatch, IAM, VPC).
• Experience working with NoSQL databases such as Elasticsearch and MongoDB.
• Experience working with messaging bus like Kafka or RabbitMQ
• Proficiency in ETL frameworks like FluentD.
• Strong debugging and system troubleshooting skills, including experience with production issues.
• Exposure to CI/CD tools (e.g., GitLab CI, Jenkins, GitHub Actions).
• Familiarity with Agile development practices and tools like JIRA.
• Experience with NoSQL databases such as Elasticsearch and MongoDB for handling unstructured or semi-structured data at scale.