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.