We are seeking an experienced KDB+/Q Developer to design, build, and maintain ultra-high-performance data platforms. You will work on systems that process large-scale real-time (tick) and historical datasets, ensuring extreme low latency and reliability for mission-critical environments such as trading, IoT, and telemetry.Key Responsibilities: Design and develop high-performance solutions in q/KDB+ for both in-memory and on-disk data structures (splayed and partitioned databases). Architect and optimize real-time data pipelines, including Ticker Plants, Chained Tickers, and Real-Time Databases (RDB). Maintain and enhance Historical Databases (HDB), ensuring millisecond-level performance over terabyte-scale datasets. Identify and eliminate performance bottlenecks across CPU, memory, and I/O layers, applying vectorized programming best practices. Develop and maintain integrations between KDB+ and external systems using Python (PyQ/EmbedPy), Java, or C++. Support production systems operating in high-pressure, real-time environments.Requirements: 5+ years of hands-on experience with KDB+ and q, including strong system design expertise. Deep understanding of vectorized programming in q, leveraging primitives such as adverbs, over, and scan. Strong knowledge of Linux/Unix environments (shell scripting, memory management, file systems). Solid understanding of low-latency architecture and hardware considerations (RAM vs SSD optimization). Proven ability to solve complex problems in real-time, high-performance systems. Fluent in English and Portuguese (mandatory).Nice to Have: Experience with messaging systems such as Kafka, Solace, or frameworks like Aqua / TorQ. Background in capital markets (Equities, FX, Fixed Income) or large-scale IoT / sensor data platforms. Experience working in mission-critical production or trading environments.Additional Information: Fully remote position (on-site presence in São Paulo is a plus). Competitive rate to be defined. Opportunity to work on cutting-edge, high-throughput real-time data systems at scale.