Senior Engineering Manager

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.