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

Data engineer (fintech) salaries in New York in 2026 typically range from $120,000 to $260,000 base, with total compensation often landing between $140,000 and $340,000+ once bonus and equity are included. If you’re in a strong fintech shop with cloud, streaming, and regulated-data experience, the upper end is very real.

Salary by Experience

A few notes on these ranges:

• •Fintech pays a premium in New York because the city is one of the biggest financial centers in the world.
• •Roles tied to payments, risk, fraud detection, market data, or lending platforms usually pay above generic data engineering roles.
• •Companies with strong bonus structures can make total comp much higher than base alone suggests.
• •Startups may offer lower base but meaningful equity; mature firms often push more into cash bonus.

What Affects Your Salary

• •

  Domain specialization matters.
  If you’ve built pipelines for payments reconciliation, AML/KYC data flows, fraud analytics, credit risk, or trading systems, you’ll usually command more than someone doing general BI ingestion work.

• •

  Cloud and streaming skills raise your ceiling.
  Strong experience with AWS/GCP/Azure, plus tools like Kafka, Spark, dbt, Airflow, Snowflake, Databricks, and real-time architecture tends to move you into senior compensation bands faster.

• •

  Regulated-data experience is valuable.
  Fintech employers pay for engineers who understand PII handling, auditability, lineage, access controls, SOC 2 constraints, and data quality in controlled environments.

• •

  Remote vs onsite changes the number.
  Fully remote roles can still pay New York rates if the company wants local talent or has a NYC presence. But some firms discount for remote hires outside the metro area; onsite or hybrid in Manhattan often keeps you closer to top-of-band offers.

• •

  Company type changes comp structure.

  • •Big banks / large fintechs: higher stability, strong bonus potential
  • •Late-stage startups: often higher upside via equity
  • •Early-stage startups: lower cash base unless heavily funded
  • •Trading/market infrastructure firms: can pay above fintech averages if latency and scale are involved

How to Negotiate

• •

  Anchor on scope, not title.
  In New York fintech especially, “data engineer” can mean anything from ETL maintenance to owning production-grade data platforms. Push the conversation toward what you’ll actually own: pipeline reliability, latency targets, governance controls, and whether you’re supporting revenue-critical systems.

• •

  Price in regulated-domain experience.
  If you’ve worked with PCI data, transaction systems, fraud models feeding production decisions, or compliance-heavy pipelines that survived audits without drama, say it plainly. That experience reduces risk for the employer and should be priced above generic engineering work.

• •

  Ask about total compensation early.
  Don’t negotiate only base salary. In fintech New York roles, bonus targets can be meaningful and equity can swing total comp by tens of thousands of dollars.

• •

  Use market comparisons from adjacent roles.
  If your work overlaps with platform engineering or ML data infrastructure — for example feature stores or real-time scoring pipelines — compare yourself to those salary bands too. Employers often budget more for “data platform” or “ML infrastructure” than for traditional ETL roles.

Comparable Roles

• •

  Analytics Engineer: typically $130K–$210K base in New York fintech
  Strong SQL/dbt-heavy roles often sit slightly below core data engineering unless they own critical metrics layers.

• •

  Data Platform Engineer: typically $170K–$240K base
  Usually pays more when the role includes infrastructure ownership, governance tooling, and developer platform work.

• •

  Machine Learning Engineer (Data-heavy): typically $180K–$260K base
  AI/ML-adjacent roles trend higher than traditional SWE when they involve model pipelines, feature engineering at scale, or production inference support.

• •

  Backend Software Engineer (Fintech): typically $160K–$235K base
  Comparable when the role touches transaction systems or internal financial workflows; pure application backend may land lower than platform/data infra work.

• •

  Data Scientist (Fintech): typically $150K–$230K base
  Often similar at mid-levels but can exceed data engineering when tied to fraud models, risk scoring, or revenue-sensitive experimentation.

If you’re interviewing in New York fintech right now and your stack includes streaming data + cloud + regulated environments + production ownership, you should be aiming near the top half of these ranges. If your background is mostly batch ETL and dashboard support without platform ownership, expect the middle of the band rather than the peak.

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By Cyprian Aarons, AI Consultant at Topiax.