Senior Data-Driven Software Engineer
Job Description
[c. $275-350k Comp Package | Remote Working - US-Based]
Are you a cloud-native software and platform engineer with solid expertise in event-driven data engineering? Our client, a global trading leader, is seeking a Senior Data Engineer to join their high-performance platform team. This cutting-edge platform underpins trading, research, and operational functions, driving pre- and post-trade activities. This is a unique opportunity to design, build, and manage state-of-the-art data systems while mentoring junior engineers and fostering a culture of engineering excellence!
Key Responsibilities:
• Design, build, and maintain a scalable, data-intensive platform used across all trading divisions
• Collaborate with the business to onboard and manage new data sources, unlocking fresh trading opportunities
• Develop solutions to organise, track, and ensure the quality of data sets
• Monitor data ingestion pipelines and implement robust quality control processes
• Mentor junior engineers, instilling best practices and upholding code quality standards
Key Requirements:
• 7+ years of experience in modern data technologies or building high-performance, event-driven distributed systems
• Expertise in Java or Scala (preferred), or Python, with a proven ability to deliver maintainable, high-quality code
• Proficiency in SQL and Shell scripting
• Strong experience with batch and real-time streaming data systems, including an understanding of their limitations
• Familiarity with cloud-native technologies for secure, scalable data processing
• Experience with advanced data processing tools (e.g., Apache frameworks), messaging/middleware, and diverse storage solutions
• Knowledge of data interchange and serialization formats and libraries (e.g., Apache, Google, JSON)
• Hands-on experience in dataflow management and orchestration tools for cloud-native environments, including batch schedulers and ETL pipelines
• Proven ability to implement schema governance, schema evolution, and data quality control processes
• (Preferred) Prior exposure to time-series data
• (Preferred) Industry expertise in financial markets, trading data, or market infrastructure, with minimal non-compete restrictions
…
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