Data Engineer at MLabs

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

21 Apr, 26

Salary

300000.0

Posted On

21 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Pipelines, Parameter Proposal Systems, Monitoring & Observability, Backtesting & Validation, Productionization, Data Engineering Fluency, AWS Mastery, Observability Expertise, Production Mindset, Statistical Models, DeFi Knowledge, Blockchain Tooling, Modern Data Stack, Economic Safety Systems, CI/CD, Grafana

Industry

IT Services and IT Consulting

Description

Senior Data Engineer (Monitoring & Parameter Systems) Location: Porto, Portugal OR New York, NY (Full-Time) Category: Engineering / Data Science Compensation: $140K - $300K We are on a simple mission: to make it possible for anyone with a digital wallet to trade stocks, commodities, currencies, and crypto with full transparency. We are replacing the opaque, offshore brokerage model with a transparent, permissionless trading stack built entirely on-chain. Every trade, deposit, and withdrawal on our platform is verifiable through open, auditable code. To date, we have raised $27.9M+ from top-tier investors including General Catalyst, Jump, Susquehanna (SIG), Alliance DAO, and Balaji Srinivasan. We are seeking a Data Engineer (Monitoring & Parameter Systems) to architect and operate the analytics, observability, and parameter-proposal infrastructure that keeps our protocol safe and economically sound. You will serve as the critical bridge between protocol mechanics—such as fees, spreads, and liquidations—and production-grade data systems. Your mandate is to translate complex economic models into reliable pipelines and monitoring services that ensure the protocol remains healthy across all markets. Responsibilities Data Pipelines: Architect and maintain robust ingestion and transformation pipelines for on-chain events and market data using AWS-native services. Parameter Proposal Systems: Implement mathematical parameter models (dynamic spreads, risk limits, funding controls) as reproducible code, producing versioned artifacts for protocol upgrades. Monitoring & Observability: Design Grafana dashboards and alerting systems for protocol health and economic correctness (execution costs, fee accrual, oracle quality, etc.). Backtesting & Validation: Build testing and "replay" frameworks to validate proposed parameter changes against historical data and stress scenarios. Productionization: Package models and pipelines into reliable services with CI/CD, automated data quality checks, and continuous output monitoring. Data Engineering Fluency: Strong proficiency in Python (pandas, numpy) and SQL, with experience designing analytics schemas for time-series and high-frequency trading data. AWS Mastery: Hands-on experience with the core AWS stack, including S3, Athena/Glue, Redshift, ECS/EKS, and Lambda. Observability Expertise: Proven ability to build monitoring systems using Grafana (ideally with Prometheus/Loki), including metrics definition and incident response workflows. Production Mindset: Experience turning research-heavy logic into robust, versioned libraries/services with full CI/CD integration. Education: Degree in Computer Science, Engineering, or a related quantitative field. Preferred Qualifications: A Data Scientist mindset: Experience building/validating statistical models for parameter tuning or anomaly detection. DeFi/Trading Domain Knowledge: Familiarity with PnL, funding/rollover mechanics, and the specific "quirks" of on-chain event streams. Blockchain Tooling: Experience with indexing tools (Subgraphs, Dune, RPC parsing) and handling smart contract schema drift. Modern Data Stack: Familiarity with orchestration and quality tools like Airflow/Dagster, dbt, and Great Expectations. High-Stakes Impact: Help architect the economic safety systems for a $27M+ backed RWA protocol. Cutting-Edge Tech: Work at the frontier of blockchain technology and decentralized finance. Competitive Package: High-tier salary plus tokens and equity. Collaborative Environment: Join a team of highly skilled engineers and researchers in a flat, fast-moving structure. Flexibility: Modern work arrangements with professional development support. 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 human-resources@mlabs.city. 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 legal@mlabs.city.

Responsibilities

The Data Engineer will architect and operate analytics and monitoring infrastructure to ensure protocol safety and economic soundness. Responsibilities include building data pipelines, implementing parameter models, and designing monitoring systems.