Engineering Team Lead – Backend 239463

We're seeking an experienced Engineering Team Lead to drive the development of scalable backend services for an innovative data-driven software platform. This role combines hands-on technical leadership with team management, architecture ownership, and close collaboration with cross-functional stakeholders.

Responsibilities

• Lead a team of backend engineers, providing technical guidance, mentorship, and career development.

• Architect, build, and maintain highly scalable backend systems serving mission-critical applications.

• Define and implement technical strategies that support product growth, performance, and reliability.

• Collaborate with Product, Data, and Engineering teams to deliver impactful solutions aligned with business objectives.

• Design and optimize data storage solutions for large-scale and complex datasets.

• Take ownership of the full software development lifecycle, from planning and design through deployment and ongoing support.

• Drive engineering excellence by promoting coding standards, best practices, and continuous improvement initiatives.

• Contribute to architectural decisions related to advanced analytics, machine learning, and intelligent automation capabilities.

Requirements

• 5+ years of backend software development experience with Python.

• Previous experience building and operating SaaS platforms in production environments.

• Strong background in distributed systems, software architecture, and scalable application design.

• Solid understanding of object-oriented programming, algorithms, and data structures.

• Excellent analytical, troubleshooting, and problem-solving abilities.

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related discipline.

Preferred Qualifications

• Exposure to AI, Generative AI, or Large Language Model (LLM) technologies.

• Experience working with MongoDB or other NoSQL databases.

• Hands-on experience with cloud-based infrastructure and services.

• Familiarity with modern DevOps practices and deployment pipelines.