AI ML Data Engineer for ADAS Sr Backend Developer

On-siteSeniorData Engineerposted 1mo ago

✦Role summaryAI-generated

Senior backend engineer specializing in Python/FastAPI for scalable, containerized ADAS systems with Kafka-based event-driven pipelines, bridging ML/data teams with cloud-native infrastructure.

Skills required

Python FastAPI Microservices Docker Kubernetes Kafka Restful api Event driven architecture Cloud computing Data pipelines SQL NoSQL CI/CD AWS Azure GCP Flask Django Data modeling

About this role

We are looking for an experienced Senior Backend Developer to architect, build, and optimize high‑performance backend systems. The ideal candidate is a strong Python developer with hands‑on experience in FastAPI, microservices, containerization, cloud platforms, and event‑driven architectures.

Key Responsibilities

Design, develop, and maintain scalable backend services using Python and FastAPI.
Build reliable and efficient RESTful APIs and backend components.
Implement and manage containerized applications using Docker and orchestrate using Kubernetes.
Work with Apache Kafka for real‑time messaging, data pipelines, and event-driven processing.
Collaborate with cross-functional teams to define technical requirements and deliver new features.
Work with both SQL and NoSQL databases, applying performance optimization techniques for high‑volume data.
Monitor, troubleshoot, and optimize system performance and reliability.
Participate in code reviews, contribute to best practices, and drive knowledge sharing.
Implement and maintain CI/CD pipelines to ensure smooth and automated deployment processes.
Work with cloud platforms such as AWS, Azure, or GCP for scalable infrastructure and services.

Qualifications

5–10 years of hands-on experience in backend development with a strong focus on Python.
Proven experience with FastAPI, Flask, or Django, and building production-grade RESTful APIs.
Strong knowledge of SQL and NoSQL databases, along with data modeling and optimization techniques.
Proficiency in Docker and Kubernetes for containerized workloads.
Experience with Apache Kafka or similar message brokers.
Solid understanding of CI/CD tools and practices (GitHub Actions, GitLab CI, Jenkins, etc.).
Hands-on experience with cloud platforms (AWS, Azure, or GCP).
Strong analytical and problem‑solving skills.
Excellent collaboration and communication abilities.
Ability to thrive in a fast-paced, dynamic environment.