We are Billie, the leading provider of Buy Now, Pay Later (BNPL) payment methods for businesses, offering B2B companies innovative digital payment services and modern checkout solutions. We are to create a new standard for business payments and have made it our mission to simplify the purchasing experience for all businesses making it a tool for growth. Our solutions are based on proprietary, machine-learning-supported risk models, fully digitized processes and a highly scalable tech platform. This makes us a deep-tech company building financial products, not the other way around. We love building simple and elegant solutions and we strive for automation and scalability.

WHO WE ARE LOOKING FOR:

• OLAP systems (e.g., Snowflake or similar technologies)
• Data Orchestration tools (e.g., Airflow or equivalent)
• Data Transformation frameworks (e.g., DBT or similar)
• Cloud platforms (e.g., AWS or other cloud services)
• Streaming Frameworks - Flink

We’re seeking a talented and passionate Data Engineer to join our dynamic team.
In this role, you’ll collaborate with fellow data engineers to design, implement, and maintain robust data pipelines and infrastructure that power our organization’s data-driven decision-making.
You’ll work closely with cross-functional teams, including data scientists, analysts, and software engineers, ensuring our data processes are available, reliable, and efficient.
This position offers significant autonomy, allowing you to shape our data engineering strategies and make impactful decisions.

As our new Data Engineer, you will:

• Design and manage data infrastructure components, including databases, data warehouses, and data lakes, to ensure high availability, reliability, and performance.
• Contribute to technical strategy by collaborating with stakeholders to define and implement data engineering roadmaps aligned with business goals and industry best practices.
• Partner with cross-functional teams to understand data requirements, define data models, and deliver actionable insights that drive business decisions.
• Establish and maintain data quality standards, implementing monitoring and alerting systems to proactively identify and address issues.
• Ensure compliance with data privacy regulations (e.g., GDPR, CCPA) and industry standards, implementing data governance policies and security measures to protect sensitive data assets.