Senior Data Engineer

MLabs; New York (NY); Hybrid; USD 180,000 - 320,000; Full time

Benefits offered by this job

Equity ownership package

Network token allocation

Competitive base salary

Job summary

MLabs, a high-volume DeFi protocol, is seeking a Senior Data Engineer in New York (Hybrid) to lead data infrastructure initiatives and optimize high-throughput pipelines. You will build an advanced infra layer to empower engineering teams with self-service deployment, infrastructure requests, and monitoring capabilities.

The role focuses on scaling pipelines, reducing latency on critical paths, and instituting modern data engineering best practices across the organization.

Qualifications

• Experience with dbt or SQLMesh data modeling.
• Experience with Airflow, Dagster or Prefect.
• Experience with PostgreSQL or ClickHouse.
• Knowledge of distributed data pipelines and systems.

Responsibilities

• Optimize high-throughput data pipelines for DeFi trading infrastructure.
• Lower latency on critical path applications through architecture improvements.
• Develop and mature in-house testing and validation tooling for multi-env local runs.
• Drive organization-wide data standards and enable 90% self-service infrastructure autonomy.
• Maintain security-first approach and robust platform stability with AI tools and testing.

Skills

Data modeling frameworks

Data orchestration

Distributed systems

Tools

PostgreSQL

ClickHouse

Airflow

Dagster

Prefect

Job description

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

1. Hiring Manager Interview: Initial discussion with the Backend Team Lead.
2. Technical Interview 1: System Design session.
3. Technical Interview 2: Practical AI Coding round.
4. Final Interview: Strategy and culture alignment call with the Chief Technology Officer.

Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search.

Commitment to Equality and Accessibility

At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing [e-mail].

MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd’s Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting [e-mail].