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:

We’re seeking candidates who bring significant experience and expertise in

• Extensive experience (typically 5+ years) as a Data Engineer or Software Engineer with a strong focus on data-intensive systems.
• Proven track record of designing, building, and operating large-scale data processing systems, including significant experience with both streaming technologies (e.g., Kafka, Flink, Kinesis) and batch processing frameworks.
• Strong software engineering fundamentals and proficiency in at least one primary language (e.g., Python, Kotlin, Java, Scala), comfortable working across different languages and paradigms (including SQL).
• Demonstrated ability to design robust, scalable, and maintainable data architectures in a cloud environment (AWS or GCP preferred).
• Experience leading technical projects and making critical design decisions.
• Excellent problem-solving skills, with the ability to analyze complex requirements and devise effective solutions.
• Experience deploying and managing infrastructure using Infrastructure as Code (e.g., Terraform) and CI/CD pipelines.
• Experience or strong interest in mentoring other engineers.

IT’S GREAT IF YOU HAVE EXPERIENCE WITH ONE OR MORE OF THE FOLLOWING TOPICS:

• Deep expertise specifically with Apache Flink for complex stream processing.
• Advanced knowledge of cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and data lakes.
• Experience managing large-scale cloud deployments across services (e.g., compute, storage, networking, databases).
• Experience in productionizing machine learning models and collaborating with Data Scientists (e.g., using tools like Metaflow, Sagemaker, MLflow, Vertex AI).
• Expertise with modern data orchestration tools (e.g., Airflow, Dagster) and data transformation frameworks (e.g., dbt, SQLMesh).
• Experience with data modeling, data governance, and data quality frameworks.

Billie is looking for a seasoned and versatile Senior Data Engineer to provide technical leadership and expertise within our data platform team. This role is pivotal in shaping the future of data engineering at Billie, impacting critical systems like our ML-powered risk assessment engines and the entire data ecosystem that fuels our growth. You will tackle complex challenges across both real-time streaming and batch processing domains.
As a senior member of the team, you will not only contribute hands-on but also guide architectural decisions, mentor other engineers, and champion best practices. You’ll work closely with data scientists, analysts, software engineers, and product managers to design, build, and operate scalable, reliable, and performant data infrastructure that meets diverse business needs. This role requires a strong blend of deep technical skills, architectural vision, and leadership qualities.

As our new Senior Data Engineer, you will:

• Lead the design, implementation, and operation of complex data solutions, encompassing both real-time streaming (using technologies like Kafka/Flink) and batch processing systems.
• Architect and evolve Billie’s overall data platform, ensuring scalability, reliability, and cost-effectiveness.
• Drive technical direction and establish best practices within the data engineering team.
• Mentor and guide junior and mid-level engineers, fostering a culture of technical excellence and continuous learning.
• Collaborate with stakeholders across the business to translate requirements into robust and scalable data architectures and solutions.
• Evaluate, prototype, and recommend new technologies and approaches to keep our data platform modern and efficient.
• Champion high standards for system reliability, performance, monitoring, testing, and alerting across all data systems.
• Ensure rigorous adherence to data privacy regulations, security protocols, and industry standards.
• Participate actively in architectural reviews and technical discussions, influencing engineering-wide standards.