data engineer (payments) Salary in Stockholm (2026): Complete Guide

A data engineer (payments) in Stockholm in 2026 typically earns $62,000–$145,000 USD base salary depending on experience, company type, and how close the role is to regulated payments infrastructure. For senior candidates at fintechs, banks, and payment processors, total compensation can push higher with bonus and equity.

Salary by Experience

A few notes on these ranges:

• •Stockholm pays well for data engineering, but payments-specific experience matters more than generic ETL work.
• •If you have strong experience with Kafka, Spark, dbt, Snowflake/BigQuery, Airflow, and event-driven payment pipelines, you’ll land toward the top of the band.
• •Roles tied to fraud detection pipelines, reconciliation systems, ledgering, or card/payment processing usually pay above standard analytics engineering jobs.
• •AI/ML-adjacent data roles in Stockholm are trending higher than traditional SWE-adjacent data roles when they support risk scoring or fraud models.

What Affects Your Salary

• •

  Payments domain depth

  • •If you’ve worked on transaction processing, settlement, chargebacks, reconciliation, PSP integrations, PCI-sensitive data flows, your salary will be materially higher.
  • •Generic warehouse work is useful, but it won’t command the same premium as someone who understands payment lifecycle edge cases.
• •

  Industry premium

  • •Stockholm has a strong concentration of fintech and banking, and that creates a real premium for payments talent.
  • •Banks tend to pay less cash than top fintechs, but they may offset with stability and stronger benefits.
  • •Payment companies and high-growth fintechs usually pay the best base salaries in this niche.
• •

  Company stage

  • •Large banks: lower upside on base salary, stronger job security.
  • •Scale-ups: often the best mix of salary growth and scope.
  • •Mature fintechs: highest competition for experienced hires; they’ll pay for someone who can own production pipelines end to end.
• •

  Cloud and platform stack

  • •Engineers who can run production workloads on AWS or GCP, manage orchestration with Airflow/Dagster, and design reliable streaming systems get paid more.
  • •If you only do SQL transformations and dashboard support, you’ll sit below market for a payments specialist.
• •

  Remote vs onsite

  • •Fully remote roles sometimes compress salary bands if the company is hiring across Sweden or Europe.
  • •Onsite or hybrid roles in Stockholm often pay slightly better when they require collaboration with product, risk, compliance, and finance teams.

How to Negotiate

• •

  Anchor on business-critical outcomes

  • •Don’t sell yourself as “a data engineer.”
  • •Sell yourself as someone who improves payment reliability, reconciliation accuracy, fraud signal quality, and incident recovery time.
  • •In payments roles, business impact maps directly to compensation.
• •

  Bring domain-specific proof

  • •Be ready to talk about:
    • •reducing failed pipeline runs during peak transaction windows
    • •building idempotent ingestion for payment events
    • •handling late-arriving events and duplicate transactions
    • •supporting audit-ready data lineage
  • •The more you speak their language—settlement files, ledger consistency, chargeback flows—the easier it is to justify top-of-band pay.
• •

  Negotiate total comp separately from base

  • •Stockholm employers may present a clean base number first.
  • •Push on:
    • •annual bonus
    • •sign-on bonus
    • •equity
    • •pension contributions
    • •extra vacation days
    • •relocation support
  • •For senior candidates in fintechs, equity can make a meaningful difference even if base looks similar across offers.
• •

  Use market scarcity correctly

  • •Payments data engineers are harder to find than generalist analytics engineers.
  • •If you have experience with regulated environments or high-volume transaction systems, say that clearly early in the process.
  • •Scarcity matters more than years alone.

Comparable Roles

Here are related titles you can use as benchmarks when comparing offers:

• •

  Data Engineer — $68,000–$120,000
  Broader role without deep payments specialization. Usually lower than payments-focused positions.

• •

  Analytics Engineer — $70,000–$115,000
  Strong SQL/dbt focus. Pays well in product-heavy teams but usually below streaming/data platform roles.

• •

  Senior Data Platform Engineer — $110,000–$140,000
  Closer to infrastructure ownership. Often overlaps with cloud architecture and observability work.

• •

  Fraud Data Engineer — $105,000–$145,000
  Usually pays at or above payments data engineering because it sits directly on revenue protection.

• •

  Machine Learning Engineer (Risk/Fraud) — $120,000–$160,000
  Often higher paid than traditional data engineering because AI/ML skills carry a premium in Stockholm’s fintech market.

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.