Senior Data Engineer

NxT Level • New York, NY

5d

About The Position

Our client is scaling a modern data platform across more business domains, pipelines, and internal stakeholders. As the platform grows, the architectural decisions made today will directly impact reliability, cost, developer experience, and long-term technical debt. The team is looking for a senior data engineer who can help shape the foundation of the platform while still staying hands-on with the work. This is an opportunity to join a data organization that values strong technical judgment, practical execution, and long-term platform health. Our client is hiring a Senior Data Engineer II to own and evolve data pipeline architecture across core platform domains. This is not a whiteboard-only architecture role. This person will still be hands-on — writing pipelines, debugging production issues, improving observability, and shipping code alongside the team. What makes this role senior is the scope. You’ll make independent architectural decisions, evaluate platform tradeoffs, influence how Analytics Engineering, Data Science, and Engineering teams build on the data platform, and serve as a trusted technical partner when complex design decisions need a second opinion.

Requirements

• Senior-level data engineering experience with strong ownership of production data pipelines
• Experience designing data pipeline architecture across ingestion, transformation, modeling, and serving layers
• Strong hands-on experience building, debugging, and operating production data systems
• Ability to evaluate platform tradeoffs across scalability, cost, reliability, freshness, and simplicity
• Experience improving warehouse performance, compute efficiency, cost controls, and access control patterns
• Strong understanding of data observability, testing, alerting, CI/CD, and production reliability
• Ability to lead large technical initiatives across multiple teams and stakeholders
• Strong technical judgment and the ability to make architectural decisions independently
• Experience partnering with Analytics Engineering, Data Science, Engineering, Product, or business stakeholders
• Ability to mentor other data engineers and influence technical direction without relying on formal authority
• Interest in using AI tools to improve data engineering workflows, automation, and team leverage

Nice To Haves

• Experience with modern cloud data warehouses and data platform architecture
• Experience leading platform modernization, cost optimization, or data reliability initiatives
• Experience building internal tooling for data teams
• Experience improving developer experience for analytics engineering or data science teams
• Experience applying AI-assisted workflows to data engineering, orchestration, observability, or quality automation
• Experience working in high-growth marketplace, consumer technology, fintech, real estate technology, or data-heavy product environments

Responsibilities

• Own and evolve data pipeline architecture across ingestion, transformation, modeling, and serving
• Make project-level architectural decisions independently
• Evaluate tradeoffs across freshness, cost, scalability, reliability, and simplicity
• Lead platform-level improvements across warehouse cost management, compute efficiency, and access control
• Treat reliability, observability, and cost efficiency as core design constraints
• Identify and lead technical initiatives that improve the long-term health of the data platform
• Proactively surface investments across orchestration, CI/CD, data access, and developer experience before they become blockers
• Drive large, complex technical projects or multiple cross-functional initiatives at once
• Own outcomes across projects that span Data, Analytics, Data Science, Engineering, and Product teams
• Lead monitoring and testing strategy for your domain
• Close observability gaps, build proactive alerting, and help resolve the hardest production issues
• Influence technical decisions and architectural direction beyond the Data & Analytics team
• Partner directly with Engineering, Product, and Design stakeholders on infrastructure decisions that impact business roadmaps
• Mentor data engineers and analytics engineers through architecture reviews, modeling decisions, and technical guidance
• Integrate AI meaningfully into data engineering workflows
• Build tooling and automation that creates leverage for the broader team, not just individual productivity
• Coach others on effective, validated use of AI in data engineering workflows

Benefits

• Own meaningful architecture across a growing data platform
• Stay hands-on while influencing platform direction at a senior IC level
• Work closely with Analytics Engineering, Data Science, Engineering, and Product teams
• Lead high-impact initiatives across reliability, observability, cost, access control, and developer experience
• Help reduce long-term technical debt before it becomes a major blocker
• Mentor other engineers and become a trusted technical voice across the organization
• Build AI-enabled tooling and automation that creates leverage for the entire data team

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed