Lead Data Engineer

About Us
Immersve are a global Mastercard issuer. Our partners are crypto and fintech companies. Together we issue Mastercard cards backed by on-chain funds, enabling cardholders to make real-world purchases in the same way they would with a traditional bank's Mastercard.
Our partners bring the people and the wallets. We bring the card programme, issuing, scheme relationships, and the compliance framework behind them.
Making that feel ordinary is the hard part. Blockchains, card schemes and financial regulators were built in different decades by people who never expected to meet each other, and our platform is where they do. None of it is solved by following a manual. It takes people who can work the problem out from first principles, and then build it.
The Role
As a Data Engineer, you will be responsible for designing and building data solutions to meet the needs of stakeholders inside and outside the business. Your role includes “telling stories” with data: being able to help others understand the insights that are being revealed and the meaning of them in terms of business value.
You will collaborate with senior leaders and a skilled team of engineers in a highly collaborative, remote-first environment based in New Zealand.
About You
You are first and foremost a team player. 🥰
You need to have:
Solid experience in data engineering, with a track record of managing successful data insight projects
Confidence to make Node.js application changes to capture missing data.
Excellent communication, stakeholder management, and problem-solving skills
Proficient in modern software delivery project management tools and methodologies
Ability to work collaboratively in a fast-paced, cross-functional environment
Ideally you have:
Worked on a successful, highly scaled international project with a large user base.
Strong understanding of financial services, payment processing, and issuing as a service models
You embrace a continuous delivery mindset — working in small batches, verifying the correctness of your work at each increment. You are comfortable contributing to high level technical designs and mentoring others.
Key Considerations for the role:
Design and build data pipelines, data visualisations, and data products that bring together data that includes cardholder/user behaviour, transactions, financial information (specifically unit economics), KYC/AML information
Design and build appropriate and relevant dashboards, visualisations, and tabular extracts that answer questions for the business
Lead evaluation and selection of tools and technologies to lift data capabilities
Be a champion of data quality across Engineering and, as appropriate, across the business
Understand what insights are required so we can successfully deliver our product offering with scale, in a heavily regulated industry
Document and embed best practice processes, including: performance testing, automated testing, load testing, acceptance testing, non-technical testing etc
Play an active role in enabling our Continuous Integration and Continuous Deployment practices with speed and ease of delivery through our pipelines
Contribute to testing deliverables by both building test plans and doing testing yourself as well as also showing others how to
Develop and monitor key outcomes to measure the success of data engineering
Tech Stack
Below are some of the technologies we are building with:
BI tool experience (e.g. Quicksight)
Dynamo DB, SQL OLTP OLAP database expertise (e.g. Clickhouse, Redshift etc)
ETL, data pipelines and real-time streaming, data transformation (e.g. Kinesis)
Node JS, Javascript/Typescript
Orchestration (cronjobs, helm deployed jobs)
Some of our perks
Flexibility - Work from anywhere in NZ for that perfect work-life balance and 5 weeks Annual Leave; ⚖️
Support - People first approach 💗 with investment in personal growth, ongoing learning and development; 📚
Reward - Competitive salary and share options; 📈
Technology - MacBook Pro (Silicon 🤩) and a home office budget. ⌨️
Application Process
Two interviews, one technical task. First is a general interview, then the tech task. The second interview is technical, going over the task and discussing other technical questions.

Work arrangement
No