data engineer (payments) Salary in USA (2026): Complete Guide
Data engineer (payments) salaries in the USA for 2026 typically range from $110,000 to $240,000 base salary, with total compensation often landing higher once bonus and equity are included. For strong payments platforms, fintechs, and large banks, senior and principal offers can push into the $250,000+ total comp range.
Salary by Experience
| Experience Level | Typical Base Salary (USD) | Notes |
|---|---|---|
| Entry (0-2 yrs) | $110,000 - $140,000 | Usually at banks, payment processors, or fintechs with strong SQL/Python fundamentals |
| Mid (3-5 yrs) | $140,000 - $175,000 | Common range for engineers owning pipelines, reconciliation jobs, and event-driven data flows |
| Senior (5+ yrs) | $175,000 - $220,000 | Higher end if you own ledgering, settlement data, fraud telemetry, or compliance-heavy systems |
| Principal (8+ yrs) | $210,000 - $240,000+ | Often includes architecture ownership, cross-team design authority, and platform strategy |
What Affects Your Salary
- •
Payments domain depth
- •If you’ve worked on card authorization, clearing and settlement, chargebacks, ledgering, ACH/RTP/Wire flows, or merchant reporting, you’ll usually command more.
- •Generic data engineering is common. Payments-specific data engineering is harder to hire for.
- •
Industry premium
- •In the USA, fintech and large payment networks usually pay more than traditional enterprises.
- •Banks pay well too, but compensation can lag top fintechs unless the role is tied to a critical platform or regulatory program.
- •
Data stack complexity
- •Engineers working with Kafka, Spark/Databricks, Flink, Airflow/Dagster, Snowflake/BigQuery/Redshift, and real-time streaming systems tend to earn more.
- •Batch-only ETL roles usually sit lower unless they support mission-critical financial reporting.
- •
Risk and compliance exposure
- •If your work touches PCI DSS, SOX controls, AML/KYC reporting, audit trails, or financial reconciliation at scale, that adds value.
- •Companies pay for engineers who can build reliable systems under regulatory scrutiny.
- •
Location and remote policy
- •New York City, Bay Area, Seattle, and some remote-first fintechs still set the top of market.
- •Fully remote roles may normalize pay across regions unless the company uses location-based bands.
How to Negotiate
- •
Anchor on business impact, not pipeline count
- •Don’t say you “built ETL jobs.” Say you reduced settlement breaks by X%, improved transaction latency by Y ms, or cut reconciliation effort by Z hours per week.
- •Payments hiring managers care about reliability metrics because failures hit revenue fast.
- •
Show domain-specific ownership
- •Bring examples of handling duplicate transactions, late-arriving events, idempotency issues, chargeback workflows, or ledger consistency.
- •That’s what separates a generalist from a payments engineer.
- •
Ask about total comp structure
- •Base salary matters less if bonus and equity are weak.
- •Compare base + annual bonus + RSUs + sign-on bonus + refreshers before accepting an offer.
- •
Use competing market signals carefully
- •If you have offers from fintechs or infrastructure-heavy companies like Stripe-style platforms or payment processors like Adyen-like competitors in the US market segment, use them as leverage.
- •Keep the negotiation factual. State your current range expectation based on scope and risk profile.
Comparable Roles
- •
Data Engineer — Fintech: $130K-$230K base
- •Similar stack and often slightly broader product analytics scope
- •
Analytics Engineer — Payments: $120K-$190K base
- •Usually lighter on infrastructure work; more dbt/warehouse modeling
- •
Backend Engineer — Payments Platform: $150K-$240K base
- •Often pays more if the role includes transaction processing or ledger services
- •
Machine Learning Engineer — Fraud/Risk: $170K-$260K base
- •AI/ML-adjacent roles trend higher because they combine data engineering with model deployment and real-time decisioning
- •
Data Platform Engineer — Financial Services: $150K-$235K base
- •Strong overlap with governance-heavy systems and enterprise-scale data infrastructure
If you’re targeting this role in the USA in 2026, aim for companies where payments is core revenue infrastructure. That’s where salary bands get meaningfully higher than generic data engineering.
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