◆ DATA ENGINEERING × FINTECH

Data engineering development for fintech

ETL, warehouses, lakehouses, real-time pipelines. We design for query cost, freshness SLOs, and analyst happiness. Tuned for fintech — Payments, lending, custody, neobank rails, embedded finance. Engineered for regulated environments — FCA, FinCEN, MiCA, MAS.

◆ WHY MIR

Why teams pick us

Fintech-grade engineering

Payments, lending, custody, neobank rails, embedded finance. Engineered for regulated environments — FCA, FinCEN, MiCA, MAS.

Data engineering where it counts

ETL, warehouses, lakehouses, real-time pipelines. We design for query cost, freshness SLOs, and analyst happiness.

Senior team, no pyramid

9+ years building outsourced product teams. Every engineer is a senior shipping production code — not a 5-person team with one architect on top.

◆ FINTECH PAIN POINTS WE SOLVE

Where Data engineering meets fintech

Double-entry ledgers that survive audits

We've shipped this in production. We design for it from day one — not as a retrofit.

Idempotent payments + reconciliation

We've shipped this in production. We design for it from day one — not as a retrofit.

KYC/KYB integrated without UX collapse

We've shipped this in production. We design for it from day one — not as a retrofit.

Regulator-ready audit trails

We've shipped this in production. We design for it from day one — not as a retrofit.

◆ STACK

What we build with

dbt Snowflake / BigQuery / DuckDB / Redshift Airbyte / Fivetran / custom CDC Kafka / Kinesis Dagster / Airflow Great Expectations / dbt tests
◆ PROCESS

How we ship

  1. Audit current pipelines — cost, freshness, ownership, debt.
  2. Design the warehouse layer with reverse-ETL in mind.
  3. Add data quality tests + lineage from day one.
  4. Ship with self-serve docs + a query-cost dashboard.
◆ START A PROJECT

Tell us what you're building

We respond within 24 hours. NDA available on request.