Senior Data Engineer

MLabs

Senior Data Engineer spearheading data infrastructure initiatives for a high-volume decentralized finance protocol. Optimizing data processing, establishing best practices, and ensuring system reliability.

Posted 7/30/2026full-timeNew York City • New York • 🇺🇸 United StatesSenior💰 $180,000 - $320,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in refining and scaling high-throughput data pipelines while ensuring security and stability. Proficient in data modeling frameworks and orchestration platforms, with a strong focus on optimizing system performance and enabling self-service infrastructure.

Highest-signal resume keywords

Data Modeling FrameworksData Orchestration PlatformsPostgreSQLClickHouseAI Acceleration Tools

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data ModelingData Pipeline ArchitectureDistributed SystemsSystem OptimizationApplication Code Development

Soft Skills

Cross-Functional CollaborationGuidance and Mentorship

Tools & Technologies

DbtSQLMeshAirflowDagsterPrefect

Industry Keywords

High-Throughput Data PipelineSecurity TestingPlatform StabilityTest SuitesSelf-Service Infrastructure

Tech Stack

Tools & technologies

AirflowDistributed SystemsDockerGoGrafanaKubernetesMicroservicesPostgresPrometheusTerraform

About the role

Key responsibilities & impact

Refine, maintain, and scale a high-throughput data pipeline to support complex, high-volume trading infrastructure.
Lower latency on critical path applications through system optimization, architectural enhancements, and direct application code development.
Mature and enhance an in-house testing and validation stack to allow developers to run applications locally across multiple environments and parallel agents.
Define organization-wide data standards, guide cross-functional software engineers on pipeline leverage, and enable 90% self-service infrastructure autonomy across the team.
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

What you’ll need

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.

Benefits

Comp & perks

Competitive base salary.
Equity ownership package.
Network token allocation.