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Wise

Senior Software Engineer II - Data Onboarding & Reporting

London
£111k – £145k/yr
Posted about 23 hours ago
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Company Description

Wise is a global technology company, building the best way to move and manage the world’s money.

Min fees. Max ease. Full speed.

Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.

As part of our team, you will be helping us create an entirely new network for the world's money.

For everyone, everywhere.

Job Description

More about our mission and what we offer.

About The Role

Wise is on a mission to create money without borders—making it instant, transparent, and eventually free. To support this rapid global growth, our Finance Squad ensures that our financial processes run in an efficient, scalable, and controlled manner.

We are looking for a talented Senior Software Engineer II to join our Data Onboarding Team in London. In this role, you will be the driving force behind building, scaling, and optimizing the critical data pipelines on top of our Lakehouse (Trino + Iceberg) infrastructure following a strict Medallion Architecture (Bronze, Silver, Gold layers). You will build robust data pipelines that serve as the foundational bedrock for reporting and assurance across the entire Finance squad.

The Finance Squad is responsible for steward-shipping the financial truth of Wise. The Data Onboarding team operates alongside Core Accounting, Finance Implementation, and Data & Assurance. Our team's mandate is to abstract product complexity and build reusable, domain-agnostic stream-enrichment pipelines. We handle high-throughput financial event data (processing hundreds of millions of events daily) to bridge the gap between immutable product events and audit-ready data structures.

What will you be working on?

Technical Leadership & Pipeline Engineering

  • Lakehouse Architecture: Design, build, and optimize robust end-to-end data pipelines on top of our Trino + Iceberg Lakehouse stack.
  • Medallion Implementation: Own the extraction, cleaning, and modeling layers to progressively refine raw event logs (Bronze) into verified subledgers (Silver) and structured Gold metrics.
  • Stream Processing: Work closely with high-throughput messaging queues (Kafka) and real-time computation models to maintain our data freshness SLAs.
  • Data Quality & Assurance: Embed rigorous, automated reconciliation checks within the data pipelines (e.g., balance and double-entry validations) to catch data discrepancies before they reach financial reporting layers.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

Strategic Impact & Collaboration

  • Product & Stakeholder Alignment: Partner directly with finance controllers, analysts, product, and engineering to turn complex corporate finance needs into production-ready data schemas.
  • Platform Alignment: Address data scaling constraints, structural technical debt, and compute optimizations to directly align infrastructure costs with Wise's financial targets.

Mentorship & Engineering Excellence

  • Upskilling: Assist and coach mid-level/junior engineers within the team, performing thorough code and technical design reviews.

Must Haves (Hard Skills)

  • Data Lakehouse Mastery: Proven experience building data infrastructure using Trino / Presto and open table formats like Apache Iceberg or Delta Lake.
  • Advanced Data Modeling: Deep expertise in Medallion Architecture patterns, Star Schemas, and processing semi-structured financial data logs (JSON/Avro).
  • Robust ETL/ELT Orchestration: Expert proficiency in data transformation engines (such as dbt) and scheduling tools (such as Airflow).
  • Stream/Message Queues: Solid understanding of event-driven architectures and streaming processing via Apache Kafka.
  • Strong Programming Foundations: Proficiency in Python, SQL, or an Object-Oriented language (Java/Scala).

Nice to Haves

  • Experience operating data assets within a regulated SOX/PCAOB compliance environment.
  • Familiarity with cloud data warehouses (e.g., Snowflake) and cloud compute orchestration.
  • Prior domain exposure to financial flows, double-entry ledger systems, or accounting integrations.

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Soft Skills

  • A strong sense of long-term technical ownership.
  • Excellent communication skills with the ability to bridge technical engineering realities with financial analyst requirements.

What We Offer / Selling Points

  • The rare opportunity to help engineer the core "Engine of Trust" for a fast-growing global fintech moving billions in cross-border volume.
  • A chance to work beyond isolated data pipelines, building reusable libraries and system-wide framework layers rather than bespoke, one-off fixes.
  • Direct interaction and collaboration with top-tier product minds, data platform engineers, and global financial stakeholders.

Interested? Find out more:

  • How we work – a practical guide
  • DEI @ Wise
  • Wise Tech Stack (2025 update)

What Do We Offer

  • Starting salary: £111k - £145k + RSUs
  • Wise Benefits
  • Paved Paths: Create structured framework documentation and automated tooling to reduce onboarding friction for new data sources.
  • See what it's like to work at Wise London!
  • Our Engineering career map - Wise Engineering

Additional Information

For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.

We're proud to have a truly international team, and we celebrate our differences.

Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.

If you want to find out more about what it's like to work at Wise visit Wise.Jobs.

Keep up to date with life at Wise by following us on LinkedIn and Instagram.

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Skills

Trino
Apache Iceberg
Medallion Architecture
Apache Kafka
Python
SQL
dbt
Airflow
Data Modeling
ETL/ELT
Java
Scala
Star Schema
Stream Processing
Data Lakehouse
Financial Data Processing

Location

London, England, United Kingdom

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