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.

BONUS SKILLS (NICE TO HAVE):

• Experience with stream processing frameworks like Apache Flink
• Familiarity with cloud-based analytical data warehouses (Snowflake, BigQuery, Redshift, Clickhouse)
• Experience managing infrastructure on cloud platforms (AWS, GCP) using tools like Terraform
• Knowledge of integrating machine learning models into production systems
• Experience with data orchestration tools (Airflow, Dagster)
• Understanding of data transformation frameworks (dbt, SQLMesh)

ABOUT THE ROLE:

We’re seeking a talented and passionate Mid-Level Data Engineer to join our dynamic team at Billie. You’ll work on our most critical systems, including our ML-powered risk assessment engines and the underlying data infrastructure, with a particular focus on real-time data processing capabilities.
This position offers significant autonomy, allowing you to shape our data engineering strategies and make impactful decisions.

YOUR RESPONSIBILITIES:

• Design, build, and maintain scalable and reliable real-time data streaming pipelines, with a focus on technologies like Kafka
• Partner with cross-functional teams (data scientists, analysts, software engineers) to implement data infrastructure that powers critical business decisions
• Work with stakeholders to understand business priorities and develop solutions that solve actual problems
• Optimize streaming applications for latency, throughput, and reliability
• Propose innovative solutions and participate in architectural discussions
• Ensure system reliability and compliance with data privacy regulations (like GDPR)