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.