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
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.
- (Good to have) Experience leading Data Engineering teams, including ETL pipeline development. 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. 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. 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. Cross-functional Collaboration
- Work closely with Product Managers, Business Stakeholders, and QA teams.
- Lead discussions on bugs, technical challenges, and product improvements.
Requirements
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.