Job Description:

We are seeking a proactive and experienced Engineering Manager to lead and scale our dynamic engineering team. This is a hands-on leadership role responsible for ensuring the timely delivery of high-performance, AI/ML-powered Data Analytics solutions.

Key Responsibilities:

1. Team Leadership & Mentorship:

- Lead, mentor, and grow a high-performing engineering team.

- Drive performance management including quarterly appraisals.

- Manage resource planning, hiring, and team structure.

- Experience leading Data Engineering teams, including ETL pipeline development (Good to have).

2. Agile & Delivery Management:

- Facilitate Agile ceremonies: daily standups, sprint planning, and retrospectives.

- Plan and manage sprints, monitor velocity, and track delivery metrics.

- Ensure alignment with the product roadmap and timely feature delivery.

- Balance task allocation and team workloads effectively.

3. Hands-On Technical Oversight:

- Be hands-on when required in Python-based projects and microservices.

- Enforce coding standards and modern development practices.

- Review code and ensure delivery of maintainable, high-quality software.

- Troubleshoot and resolve performance, scalability, and deployment issues.

4. Architecture & Deployment:

- Own solution architecture with a focus on scalability, security, and performance.

- Oversee containerization and deployment processes, including Docker-based on-premise deployments.

- Collaborate with DevOps to ensure smooth CI/CD and version control practices.

5. Cross-functional Collaboration:

- Work closely with Product Managers, Business Stakeholders, and QA teams.

- Lead discussions on bugs, technical challenges, and product improvements.

Required Skills & Qualifications:

- 15+ years of software development experience, including 4+ years in a leadership role.

- Strong Python development experience, especially in scalable, production-grade systems.

- Proficient in Python-based frameworks such as Django, Flask, and FastAPI.

- Experience with Elasticsearch for search and analytics use cases.

- Hands-on experience in Docker and on-premise deployment of enterprise products.

- Familiarity with PostgreSQL and NoSQL databases.

- Good understanding of data engineering pipelines, ETL processes, and related tools (good to have).

- Strong background in Agile methodologies, sprint planning, and delivery oversight.

- Experience with version control systems like Git and CI/CD tools.

- Solid grasp of scalable architecture, high availability, and system performance optimization.

- Excellent communication, leadership, and problem-solving abilities.