Full Stack Data Engineer

Combining equal expertise in traditional finance and digital asset treasury solutions, Orbital is a trusted and regulated partner for global financial management.

Until now, multinationals have been forced to choose their finance tools piecemeal. We provide our clients with all they need to run their financial operations from a single interface; multi-currency accounts, custody vaults, international payments and FX supporting 30+ fiat and exotic currencies, and crypto-commerce C2B payments.

What is our mission?:

Orbital is on an exciting mission to revolutionise global cross-border payments by innovatively combining traditional fiat banking rails with stablecoins over blockchain rails for a variety of use cases. Our class leading B2B payments platform offers multi-currency e-money accounts (corporate IBANs) combined with a suite of digital assets services. Our company sits at the frontier of payments & fintech, by intersecting blockchain and traditional (fiat) financial services, and is leading the way to bridging those two worlds for corporate enterprises globally.

We believe blockchain technology is firmly here to stay, and we want to be the first to bring a combined offering of fiat & crypto payment services under one exciting platform. Learn more about our team and company storyhere.

What is the purpose of this role in the delivery of our mission?

We’re looking for a Full-Stack Data Engineer who can design, build, and optimize modern data systems from the ground up. You’ll own the full data lifecycle—from architecting databases to building ETL pipelines, writing advanced queries, and enabling data-driven decision-making through powerful insights.

This role blends traditional data engineering with a strong analytics mindset. You’ll collaborate closely with engineering, product, and compliance teams to ensure clean, accessible, and scalable data flows across our platform.

What are the key responsibilities of the role?

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• Design and develop scalable, reliable data architectures and storage solutions (SQL, NoSQL, etc.)

  
  

• Build and maintain robust ETL/ELT pipelines to ingest, transform, and enrich data from multiple sources

  
  

• Write performant SQL queries for reporting, dashboards, and ad-hoc analysis

  
  

• Develop and optimize data models for both operational and analytical use

  
  

• Collaborate with analysts and stakeholders to define metrics, KPIs, and data definitions

  
  

• Implement data validation, monitoring, and observability across pipelines

  
  

• Support data visualization efforts via BI tools (Metabase, Power BI or custom dashboards)

  
  

• Ensure data security, governance, and compliance across all systems

  
  

What is the scope of accountability for the role?

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• Design, develop, deploy and maintain mission critical data applications

  
  

• Delivery of various data driven applications

  
  

• Develop and owning data models, dashboard and reporting

  
  

• Business analysis and the query of databases

  
  

What are the essential skills, qualifications and experience required for the role?

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• 3+ years of experience in data engineering or similar roles

  
  

• Strong SQL skills and experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server)

  
  

• Experience with cloud data platforms (AWS Redshift, Stich, Airbyte, Athena, Glue, S3)

  
  

• Proficient in Python or another data scripting language

  
  

• Experience with orchestration tools (e.g., Airflow, Prefect, Dagster)

  
  

• Familiarity with data warehousing, data lakes, and stream processing (Kafka, Spark, etc.)

  
  

• Understanding of data modelling techniques (e.g., star/snowflake schema, normalization)

  
  

• Ability to communicate complex data concepts to non-technical stakeholders

  
  

• You have strong analytical, organisational, and prioritisation skills, and a belief in writing documentation as part of writing code

  
  

What are the desirable skills, qualifications and experience that would be beneficial for the role?

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• Data Ingestion: AWS Kinesis/Firehose

  
  

• Data Transformation: DBT (Data Build Tool)

  
  

• Familiarity with DevOps/data infrastructure tools (Git/Bitbucket, AWS CloudFormation, AWS ECS)

  
  

• Exposure to analytics or dashboard tools (Metabase and/or PowerBI)

  
  

• Prior work in a startup, SaaS, or data-intensive environment