Backend - Engineering Manager

As a Engineering Manager, you will lead a high-impact engineering team in developing and scaling Rakuten SixthSense’s Data Observability platform. This role requires a strong technical background working high-scale systems and full-stack cloud engineering, DevOps.

Key Responsibilities

• Lead and mentor a team of 5-8 engineers, driving innovation in .
• Define and execute the technical vision for full-stack observability, ensuring high availability and performance.
• Architect and implement scalable solutions for real-time monitoring, data quality, and operational efficiency.
• Champion DevOps best practices, including CI/CD pipelines, automation, logging, and Kubernetes-based deployments.
• Ensure compliance with data governance standards, security, and scalability in hybrid cloud environments (AWS, GCP, Azure).
• Oversee end-to-end product lifecycle, from concept to deployment, ensuring seamless integration with enterprise systems.
• Collaborate with product, operations, and business stakeholders, aligning engineering efforts with strategic objectives.
• Drive Agile execution, ensuring rapid iterations, high-quality deliverables, and continuous improvement.

What You Bring

• 8-12 years of software development experience, with 4+ years in technical leadership roles.
• Expertise in Java, Spring, Hibernate, and microservices architecture.
• Experience with any cloud platforms (AWS, GCP, Azure) and hybrid cloud strategies.
• Proficiency in containerization, Kubernetes, CI/CD pipelines, and infrastructure as code.
• Full-stack experience in building RESTful APIs, real-time monitoring, and automation frameworks.
• Proven track record of leading large-scale projects and handling post-production challenges.
• Hands-on DevOps mindset, ensuring automation, quality, and reliability in data observability platforms.
• Experience using Observability Platforms.
• Excellent problem-solving, debugging, and system architecture skills.

Nice to Have

• Previous experience in AIOps, or real-time analytics platforms.
• Exposure to AI-driven automation and anomaly detection in data engineering.