Big Data & Infrastructure Engineer (Time-Series Specialist)

Description Fluent Trade Technologies is a global fintech software firm at the forefront of providing state-of-the-art technology to the world's largest global banks and hedge funds. Specializing in ultra low-latency strategy and market data solutions, Fluent is committed to delivering cutting-edge innovations to the Financial Industry. With a prominent Israeli R&D center in Jerusalem and global development centers, Fluent is a dynamic and collaborative environment. Learn more about us at www.fluenttech.net . We are seeking a Big Data & Infrastructure Architect to spearhead the data architecture for our new FX Trading Analytics platform. You will be the primary authority on the big-data engine that powers real-time and historical analysis of liquidity, fill ratios, and market impact. This is a foundational role where you will select, implement, and optimize the "brain" of our analytics suite. The position is a remote position based in Ukraine. Key Responsibilities: Architecture & Tool Selection: Evaluate and select the optimal Big Data/NoSQL engine to handle high-frequency FX market data and trade execution logs. Infrastructure Ownership: Own the end-to-end installation, configuration, scaling, and long-term maintenance of the database environment. System Design & Configuration: Design the database schema and storage strategy to support massive datasets while ensuring high availability and resilience. Query & Performance Optimization: Build and tune complex time-series queries (calculating metrics like Effective Spread and Last Look Hold Times) to ensure sub-second responses for real-time monitoring tools. Knowledge Leadership: Act as the subject matter expert, training GUI developers and team members on best practices for efficient data retrieval and interaction with the data layer. Technical Collaboration: Work closely with the team leader and GUI developers to ensure the data infrastructure perfectly supports the product requirements. Requirements Deep knowledge of at least one industry-leading Big Data or Time-Series database (e.g., ClickHouse, InfluxDB or ScyllaDB/Cassandra). Proven experience managing "high-velocity" data environments (streaming ticks, execution logs, and order book events). Strong proficiency in writing and optimizing complex queries for massive datasets (billions of rows). Extensive experience in a Linux-heavy environment with a focus on system-level performance and low-latency tuning. Ability to translate business metrics into efficient data structures without necessarily writing application-level code. Excellent English communication skills. Advantages: Experience in the financial industry (FIX protocol, FX trading, etc.). Background in high-performance hardware/software integration. Experience with scripting for automation (Python, Bash)