Senior Big Data & Time-Series Infrastructure Engineer

Senior Big Data & Time-Series Infrastructure Engineer Engineering | Remote (Europe) | Full-time About the company 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. The role We are looking for a Big Data & Infrastructure Architect to lead the data architecture of a new trading analytics platform. You will be the main authority on the data engine behind real-time and historical analysis of liquidity, order fill quality and market impact. This is a foundational position: you will choose, deploy and tune the core of the analytics product. Key responsibilities - 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. Requirements - Deep expertise in at least one leading Big Data or time-series database (for example 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 a 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) Originally posted on Himalayas