Senior Software Engineer II - Data Onboarding & Reporting

Posted Yesterday
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London, England, GBR
Hybrid
111K-145K Annually
Senior level
Fintech • Mobile • Payments • Software • Financial Services
Wise is one of the fastest growing fintechs in the world and we’re on a mission to make money without borders a new norm
The Role
Build and optimize Lakehouse data pipelines (Trino + Iceberg) using Medallion Architecture to transform high-throughput event logs into audit-ready subledgers and reporting metrics. Implement stream processing with Kafka, embed automated reconciliation/data quality checks, collaborate with finance and product stakeholders, and mentor junior engineers.
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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.

More about our mission and what we offer.

Job Description

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.

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.

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
  • #LI-AB3 #LI-Hybrid
  • 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 - https://medium.com/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.

Skills Required

  • Proven experience building data infrastructure using Trino or Presto and open table formats such as Apache Iceberg or Delta Lake
  • Deep expertise in Medallion Architecture, advanced data modeling (Star Schemas), and processing semi-structured financial data (JSON/Avro)
  • Expert proficiency with data transformation and orchestration tools such as dbt and Airflow
  • Solid understanding and experience with event-driven architectures and streaming via Apache Kafka
  • Strong programming skills in Python, SQL, or an object-oriented language (Java or Scala)

What the Team is Saying

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The Company
9,000 Employees
Year Founded: 2011

What We Do

Wise is a global technology company, building the best way to move and manage the world's money. With Wise Account and Wise Business, people and businesses can hold 40 currencies, move money between countries and spend money abroad. Large companies and banks use Wise technology too; an entirely new network for the world's money. Launched in 2011, Wise is one of the world’s fastest growing, profitable tech companies. In fiscal year 2025, Wise supported around 15.6 million people and businesses, processing over $185 billion in cross-border transactions and saving customers around $2.6 billion.

Why Work With Us

We’re truly global in who we are, how we work, and how we build. Everything we do is centred around creating a world of money that’s fast, easy, fair. And open to all. Everyone who works here owns a piece of Wise, from the work they do, to the stock they hold.

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Wise Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

We expect new joiners in the office most days to build connections and learn from colleagues for their first six months. After that, most Wisers split their working week between the office and home, typically coming in at least 12 times a month.

Typical time on-site: Flexible
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