Lead Python Software Engineer (70% Python Development | 30% Data Engineering)

We are seeking a highly skilled Lead Python Software Engineer with strong expertise in designing and developing scalable backend applications using Python. The ideal candidate should have approximately 70% hands-on Python backend development experience and 30% Data Engineering experience, including building ETL pipelines and processing large-scale data., Design, develop, and maintain scalable Python backend applications. Develop REST APIs and microservices for enterprise applications. Build and maintain ETL pipelines and data processing workflows. Collaborate with product owners, architects, and engineering teams to deliver high-quality software. Optimize application performance, scalability, and reliability. Develop cloud-native applications and deploy them using Docker and Kubernetes. Participate in architecture discussions, code reviews, and technical mentoring. Troubleshoot production issues and implement performance improvements. Follow best practices for software development, testing, security, and CI/CD. Nice to Have FastAPI PySpark Apache Airflow Kafka AWS Glue Terraform Kubernetes Redis Snowflake Databricks Google Cloud Platform Key Technologies

This posting is aligned with a role where the primary focus is Python backend engineering (70%) with supporting Data Engineering responsibilities (30%), making it suitable for candidates who are Python-first engineers with hands-on experience in data pipelines and ETL processing.

The candidate should have experience developing cloud-native applications, microservices, REST APIs, and distributed systems while collaborating with cross-functional teams in an Agile environment., 8+ years of software engineering experience with strong Python development. Expertise in Python, FastAPI, Flask, or Django. Strong experience designing and developing RESTful APIs and Microservices. Hands-on experience with Docker and Kubernetes. Experience working with AWS, Azure, or Google Cloud Platform (Google Cloud Platform). Experience with CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, or similar tools. Strong SQL skills with PostgreSQL, MySQL, or similar databases. Experience with Git and Agile/Scrum methodologies. Data Engineering Experience (30%) Experience building ETL/ELT pipelines. Hands-on experience with PySpark, Apache Spark, or similar technologies. Experience with Apache Airflow, AWS Glue, or other workflow orchestration tools. Experience processing structured and unstructured data. Knowledge of Kafka or other messaging/streaming platforms. Experience with data validation, transformation, and optimization. Preferred Skills Experience with distributed systems and event-driven architecture. Infrastructure as Code (Terraform or CloudFormation). Redis or other caching technologies. Monitoring tools such as Datadog, Prometheus, Grafana, or CloudWatch. Experience with AI/ML or GenAI integrations is a plus but not required.