Data Infrastructure Engineer Role in Global FinTech

The company is a leading product-based organization and the premier 'end-to-end' provider of data and trading technology across foreign exchange, financial, and futures markets. Its proprietary low-latency gateways empower international corporations and Tier-1 banks to execute global transactions with industry-leading speed and precision.
 

Company is looking for a Data Infrastructure Engineer for a high-impact, foundational role. In this capacity, you will serve as the primary authority on the big-data engine that drives our real-time and historical analytics. Your expertise will be critical in analyzing liquidity, fill ratios, and market impact.

      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.

   

  Nice to have:

• Experience in the financial industry (FIX protocol, FX trading, etc.).
• Background in high-performance hardware/software integration.
• Experience with scripting for automation (Python, Bash).
  
  Responsibilities:
• 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.
• 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.
• 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.
  
   Benefits:
• Standard working hours: 9-18. 
• 15 working days + public holidays weekends.
• 10 days of sick leave.
• Medical insurance compensation.
• Equipment.
• Salary reviews once a year.
  
  The market moves in milliseconds—your career should move just as fast. Send your CV.