data engineer (payments) Salary in New York (2026): Complete Guide

A data engineer (payments) in New York in 2026 typically earns $135,000 to $260,000 base salary, with total compensation often landing between $160,000 and $340,000+ once bonus and equity are included. At top-tier fintechs, payment processors, and banks with serious transaction volume, senior candidates can clear more.

Salary by Experience

A few notes on the ranges:

• •Entry-level roles are usually capped unless you already have strong Python, Spark, Kafka, or cloud warehouse experience.
• •Mid-level engineers with payments domain knowledge often jump faster than generic data engineers.
• •Senior and principal roles pay more when you own platform design, data quality for money movement, or regulatory reporting pipelines.
• •Total comp can run materially higher at public fintechs and large banks because of bonus structure and equity.

What Affects Your Salary

• •

  Payments specialization

  • •If you understand card authorization flows, ACH, RTP/FedNow, chargebacks, reconciliation, ledgering, or settlement logic, your pay goes up.
  • •Generic ETL experience is not enough at the top end. Employers pay for people who can reason about financial correctness under load.
• •

  Industry premium in New York

  • •New York has a strong concentration of banks, capital markets firms, payment companies, and fintechs.
  • •That creates a real premium for engineers who can work across compliance, risk, fraud, and transaction systems.
• •

  Company type

  • •Big banks usually pay less base than top fintechs but may offset with stability and bonus.
  • •Payment processors and high-growth fintechs often pay the most aggressively for engineers who can keep data reliable at scale.
• •

  Cloud and stack depth

  • •Strong skills in Snowflake, Databricks, dbt, Airflow, Kafka, Spark, AWS/GCP, and streaming architectures push compensation up.
  • •If you also know observability tooling and data contract patterns, you become harder to replace.
• •

  Remote vs onsite

  • •Fully remote roles may benchmark against national bands instead of New York market rates.
  • •Hybrid or onsite roles in Manhattan often pay more because employers expect local availability and faster collaboration with product/risk teams.

How to Negotiate

• •

  Anchor on business impact tied to money movement

  • •Don’t just say you built pipelines.
  • •Say you reduced reconciliation breaks by X%, improved settlement visibility by Y hours, or cut fraud-data latency from hours to minutes.
• •

  Price in payments risk

  • •Payments data engineering is not standard analytics work.
  • •You’re supporting revenue capture, ledger integrity, chargeback handling, regulatory reporting, and customer trust. That should be reflected in base salary or sign-on cash.
• •

  Ask about total comp structure early

  • •In New York finance-heavy employers often split value across base salary, annual bonus, RSUs/stock grants, and sign-on.
  • •A lower base with weak bonus is not the same as a slightly lower base with strong guaranteed cash.
• •

  Use market comps from adjacent roles

  • •If they try to anchor you below market for “just data engineering,” compare yourself to analytics engineering plus platform engineering plus payments ops complexity.
  • •A candidate who owns production-grade payment pipelines should not be priced like a dashboard builder.

Comparable Roles

• •Data Engineer — Fintech: $140k–$250k base
• •Analytics Engineer — Payments: $130k–$210k base
• •Platform Data Engineer — Banking: $150k–$240k base
• •Machine Learning Engineer — Fraud/Risk: $170k–$280k base
• •Backend Engineer — Payments Infrastructure: $160k–$270k base

If you’re choosing between these roles:

• •Go for machine learning / fraud if you want higher upside and can handle model-driven systems.
• •Go for platform data engineering if you want broader ownership and stronger long-term leverage.
• •Go for payments backend if you want closer proximity to transaction systems and usually higher technical depth expectations.

For New York specifically in 2026:

• •The market still rewards engineers who understand both data infrastructure and the mechanics of payments.
• •The best-paid candidates are not just pipeline builders; they are the people who keep financial data correct when volume spikes and edge cases show up.

Keep learning

• •The complete AI Agents Roadmap — my full 8-step breakdown
• •Free: The AI Agent Starter Kit — PDF checklist + starter code
• •Work with me — I build AI for banks and insurance companies

By Cyprian Aarons, AI Consultant at Topiax.