Data Solutions Engineer at Flatpay

Herlev, Capital Region of Denmark, Denmark -

Full Time

Start Date

Immediate

Expiry Date

10 May, 26

Salary

0.0

Posted On

09 Feb, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

TypeScript, JavaScript, Next.js, PostgreSQL, SQL, REST APIs, Git, Python, Microsoft Fabric, dbt, Vercel, Monitoring, Logging, Reliability, Code Structure, Readability, Maintainability

Industry

technology;Information and Internet

Description

About the job As a Data Solutions Engineer at Flatpay, you’ll play a key role in building and maintaining the data-powered applications that sit on top of our data platform. These apps enable internal teams to explore data, operate faster, and make better decisions in their daily work. This role sits at the intersection of data engineering and product-minded software development. You won’t be a pure software engineer, but a solutions engineer with a strong flair for rapidly building useful & maintainable data apps while ensuring solid engineering foundations, best practices, and long-term sustainability. You’ll take significant ownership of our data-powered applications helping shape standards, improve quality, and ensure that speed doesn’t come at the cost of reliability or maintainability. You’ll collaborate closely with data engineers, analytics engineers, and business stakeholders to turn data and ideas into real, usable internal products. What you'll do Design, build, and maintain data-driven applications using modern web technologies Develop frontend experiences using React and Next.js, with a focus on usability and clarity Build and integrate backend APIs and services that expose data safely and efficiently Work with and develop SQL-based data models, including data sourced from our data warehouse (Microsoft Fabric) and data models created in dbt. Improve developer experience through better project structure, conventions, and tooling Review and improve existing codebases to reduce tech debt while keeping delivery velocity high Actively participate in architectural discussions around how data apps should scale at Flatpay Who you are You are early in your career as a data or solutions engineer and enjoy building things that people use daily. You are comfortable working across SQL, data models, APIs, and frontend components, and you like turning messy or unclear requirements into simple, working solutions. You are curious, collaborative, and eager to learn. You understand that vibe coding can be a fast and creative way to build, but you also want to develop good engineering habits over time. You care about writing readable, maintainable code and are comfortable asking questions, seeking feedback, and improving through iteration. You communicate clearly in English and enjoy working cross-functionally with both technical and non-technical stakeholders. Technical skills You do not need to be an expert in everything below, but you should have experience with some and a strong willingness to learn the rest. TypeScript and JavaScript Next.js PostgreSQL and SQL REST APIs Git and basic version control workflow Python for sync scripts, data utilities, or simple backend tasks Tools and platforms you will work with Microsoft Fabric as a data source dbt as a transformation layer Vercel or similar modern deployment platforms Foundational engineering practices Basic understanding of monitoring, logging, and reliability concepts Interest in improving code structure, readability, and maintainability We’d still love to hear from you if… You do not check every box but are excited about building data-powered tools and learning by doing. You enjoy moving fast while gradually introducing structure, and you care about maintaining and improving projects over time. If you are curious, collaborative, and motivated to grow into a strong data and solutions engineer while shaping Flatpay’s internal data apps, we encourage you to apply. Why Flatpay? Contact info

Responsibilities

Design, build, and maintain data-driven applications using modern web technologies. Collaborate closely with data engineers, analytics engineers, and business stakeholders to turn data and ideas into real, usable internal products.