Big Data Engineer – Time-Series Specialist

🕒 August 21

🇺🇦 Ukraine – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 24%

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Logo of Fluent Trade Technologies

Fluent Trade Technologies

51 - 200 employees

💳 Fintech

Fintech

Fluent Trade Technologies is the fastest ‘end-to-end’ data & trading technology provider in the FX and Futures markets. Established in 2011, the company offers a comprehensive, turn-key solution for automated trading systems and brokers, enabled by a unified API that connects to over 100 FX trading venues representing over 95% of FX liquidity. Fluent Trade Technologies specializes in data processing, trading, large database warehousing, data distribution, monitoring, and pre-trade risk management solutions tailored for FX Prime Brokers and hedge fund customers, thus facilitating transactions worth billions of dollars daily.

📋 Description

• Evaluate and select the optimal Big Data/NoSQL engine to handle high-frequency FX market data and trade execution logs • Own the end-to-end installation, configuration, scaling, and long-term maintenance of the database environment • Design the database schema and storage strategy to support massive datasets while ensuring high availability and resilience • Build and tune complex time-series queries calculating metrics such as Effective Spread and Last Look Hold Times to ensure sub-second responses for real-time monitoring tools • 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 • Work closely with the team leader and GUI developers to ensure the data infrastructure supports 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 • Experience in the financial industry (FIX protocol, FX trading, etc.) • Background in high-performance hardware/software integration • Experience with scripting for automation (Python, Bash)

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