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:

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)

Originally posted on Himalayas