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.
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:
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Architecture & Tool Selection: Evaluate and select the optimal Big Data/NoSQL engine to handle high-frequency FX market data and trade execution logs.
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Infrastructure Ownership: Own the end-to-end installation, configuration, scaling, and long-term maintenance of the database environment.
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System Design & Configuration: Design the database schema and storage strategy to support massive datasets while ensuring high availability and resilience.
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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.
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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.
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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)
Originally posted on Himalayas