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Tier-1 brand, metro location, and remote flexibility increase applicant competition.
Domain-specific database observability, telemetry, and distributed systems expertise required reduces cross-industry transferability.
Explicit 10+ years plus managerial and deep backend, distributed systems, and telemetry requirements make filtering strict.
Lead and manage a full-stack engineering team (6–8 engineers) responsible for database telemetry, ingestion pipelines, AI-driven recommendation engines, and related UI workflows.
Own end-to-end delivery including sprint planning, roadmap execution, system quality, and operational excellence for critical database observability components.
Set strategic technical direction focusing on high-throughput, low-latency ingestion systems and AI technologies to evolve database observability products.
Minimum 10 years of total software engineering experience with at least 2 years managing engineering teams.
Strong technical background in backend and distributed systems using languages like Go, Java, or Python.
Foundational understanding of relational and NoSQL database engines and performance metric collection under heavy production loads.
Experience with modern development practices including CI/CD, microservices, containerization (Docker, Kubernetes), and production observability.
Experienced in leading senior-level engineers and domain experts in distributed systems and AI-driven applications, especially in observability or database engineering.
Proven success delivering complex, multi-quarter technical initiatives on schedule with high quality, managing team health and technical debt.
Familiarity with cutting-edge AI-assisted development tools and practices (e.g., Agentic AI, LLMs, MCP, Claude Code, Copilot) and real-time streaming architectures like Apache Kafka.