Senior Data Engineer

Location: New York, United States (Hybrid) Hybrid | Full-time Compensation: $180K - $320K Our client is a high-volume decentralized finance (DeFi) protocol based on Arbitrum, facilitating leveraged trading of real-world assets—including commodities, forex, indices, and equities—alongside crypto with full self-custody. The client is seeking a Senior Data Engineer to spearhead infrastructure initiatives, optimize high-throughput data processing, and establish modern data engineering best practices. This role will focus on scaling data pipelines and building an advanced infrastructure layer that empowers engineering teams with self-service capabilities for deploying applications, requesting infrastructure, and managing monitoring systems. Key Responsibilities Data Pipeline Optimization: Refine, maintain, and scale a high-throughput data pipeline to support complex, high-volume trading infrastructure Architecture & Latency Management: Lower latency on critical path applications through system optimization, architectural enhancements, and direct application code development Developer Tooling & Orchestration: Mature and enhance an in-house testing and validation stack to allow developers to run applications locally across multiple environments and parallel agents Best Practices & Self-Service: Define organization-wide data standards, guide cross-functional software engineers on pipeline leverage, and enable 90% self-service infrastructure autonomy across the team System Reliability & Security: Maintain a security-first approach by identifying attack vectors, coordinating simulated system security testing, and maintaining rigorous platform stability using AI tools and comprehensive test suites Requirements Technical Experience Strong background in data modeling frameworks (e.g., dbt, SQLMesh) and data orchestration platforms (e.g., Airflow, Dagster, Prefect) Production experience with databases such as PostgreSQL and ClickHouse Deep understanding of modern data pipeline architectures, distributed systems, and industry best practices Proficiency in leveraging AI acceleration tools while validating outputs and implementing strict code quality guardrails Professional Characteristics Security-Minded: Continuous focus on reducing attack surfaces and protecting system integrity Solution-Oriented: Focused on removing technical bottlenecks to allow software and quantitative teams to deploy rapidly Self-Directed Leadership: Capability to evaluate system requirements, prioritize high-value initiatives, and proactively propose architectural roadmaps Collaborative & Adaptable: Willingness to learn from quants, engineers, and operations teams in an evolving, high-performance environment Execution & Commitment: Ability to advocate for technical strategies during design stages, with a strong commitment to aligned execution upon final decision Benefits Competitive base salary Equity ownership package Network token allocation Interview Process Hiring Manager Interview: Initial discussion with the Backend Team Lead Technical Interview 1: System Design session Technical Interview 2: Practical AI Coding round Final Interview: Strategy and culture alignment call with the Chief Technology Officer Benefits Competitive base salary Comprehensive token and equity compensation package Opportunity to work at the forefront of global decentralized financial infrastructure Interview Process The interview process is structured across four distinct stages: Hiring Manager Interview: An introductory conversation with the Backend Team Lead Technical Interview (System Design): A deep dive into architecture and infrastructure systems design Technical Interview (AI Coding Round): A practical hands-on session evaluating technical problem-solving and AI tool utilization Final Interview: A concluding discussion focused on cultural alignment and executive evaluation with the Chief Technology Officer (CTO) Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. 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