Data Engineer

Our client is a forward-thinking finTech company dedicated to delivering innovative solutions for businesses in diverse industries.

They are looking for a disciplined, forward-thinking Backend Software Engineer to take ownership of their data infrastructure. You will be responsible for the architecture, maintenance, and optimization of pipelines that handle mission-critical financial data.

They are looking for an engineer who stays at the cutting edge of the field, specifically someone who has mastered the use of AI coding assistants (e.g., Cursor, GitHub Copilot, LLM-based refactoring) to write cleaner code, debug faster, and automate where possible.

Our client is a forward-thinking finTech company dedicated to delivering innovative solutions for businesses in diverse industries.

They are looking for a disciplined, forward-thinking Backend Software Engineer to take ownership of their data infrastructure. You will be responsible for the architecture, maintenance, and optimization of pipelines that handle mission-critical financial data.

They are looking for an engineer who stays at the cutting edge of the field, specifically someone who has mastered the use of AI coding assistants (e.g., Cursor, GitHub Copilot, LLM-based refactoring) to write cleaner code, debug faster, and automate where possible.

What you will do:

Pipeline Architecture: Design, build, and maintain scalable ETL/ELT pipelines for complex financial datasets.
Real-Time Event Ingestion: Architect and maintain an "always-on" event collection system to capture high-velocity data.
Data Integrity: Implement rigorous validation and error-handling to ensure 100% accuracy in reporting and analysis.
AI-Augmented Development: Proactively use AI tools to generate boilerplate, refactor legacy code, and accelerate the development lifecycle without sacrificing code quality.
System Optimization: Monitor and tune data warehouse performance and query efficiency.

What you will need:

• Experience: 2+ years in Data Engineering, ideally within the fintech, banking, or quantitative trading sectors.
• Tech Stack: Proficiency in Python or Typescript, and advanced SQL. Experience with async workflow libraries and tools
• Data Literacy: A solid understanding of time-series data structures
• AI Fluency: Demonstrated ability to use AI coding tools effectively. You should be able to discuss how you use prompting or AI-integrated IDEs to improve your workflow.