Senior Big Data & Time-Series Infrastructure Engineer

Our client is a global fintech software vendor supplying advanced trading technology to leading banks and hedge funds. The company specializes in high-performance, low-latency trading strategy and market data solutions for the financial industry. Engineering is spread across several international development centers, and the working culture is collaborative and fast-moving.

• Deep expertise in at least one leading Big Data or time-series database (e.g. ClickHouse, InfluxDB, or ScyllaDB/Cassandra).
• Proven experience operating high-velocity data environments (streaming ticks, execution logs, order book events).
• Strong skills in writing and tuning complex queries over very large datasets (billions of rows).
• Extensive experience in Linux-centric environments, with focus on system-level performance and low-latency tuning.
• Ability to turn business metrics into efficient data structures without necessarily writing application-level code.
• Excellent English communication skills.

Nice to have:

• Experience in financial markets or trading technology (e.g. FIX protocol).
• Background in high-performance hardware/software integration.
• Automation scripting (Python, Bash).

Architecture and technology selection:

• Assess and choose the most suitable Big Data / NoSQL engine for high-frequency market data and trade execution logs.

Infrastructure ownership:

• Take responsibility for installation, configuration, scaling and long-term operation of the database environment.

Design:

• Define the schema and storage strategy for very large datasets, ensuring high availability and resilience.

Query and performance tuning:

• Write and optimize complex time-series queries (execution quality and liquidity metrics) so that real-time monitoring tools respond in under a second.

Knowledge sharing:

• Act as the subject matter expert and coach front-end developers and teammates on efficient ways to query and use the data layer.

Collaboration:

• Work closely with the team lead and UI developers so the data infrastructure fully supports product needs.