Company Overview: Join our team at Payment’s Lab (payments-lab.com), working on EagleSense (eaglesense.ai) — an ML-driven solution designed to combat first-party fraud. We’re seeking a skilled Data Engineer to help design, implement, and manage complex data systems that form the backbone of our innovative product. The role begins part-time with the opportunity to transition to full-time as we grow together. (the indicated salary is for Part-Time) About the Role: We’re looking for a Data Engineer with hands-on experience in designing and managing scalable data infrastructure in production environments with multiple data sources. In this role, you’ll focus on creating robust systems to process, store, and deliver required data to power our machine learning models and analytics tools. Your expertise in building real-time data pipelines, optimizing databases, and managing large-scale data streams will be crucial to our success.
You’ll work closely with data scientists, engineers, and product stakeholders to ensure our data infrastructure supports efficient and reliable model deployment and performance monitoring. Responsibilities: * Design and Manage Data Systems: Set up and manage complex data streams in production, integrating multiple data sources with high reliability. * Database Management: Design and manage relational databases (e.g., Amazon RDS or Aurora) to store cumulative features and processed real-time transaction data. * Message Handling: Design and maintain SQS FIFO queues for sequencing and processing real-time transaction data. * Feature Pipelines: Create scalable feature preprocessing pipelines that handle cumulative data aggregation efficiently. * Query Optimization: Optimize database queries and implement strategies to enable high-performance analytics and reporting. * Collaboration: Work with cross-functional teams, including data scientists and product managers, to align data engineering efforts with business goals. * Performance Monitoring: Set up and maintain speed tracing and performance monitoring of the data pipelines to ensure real-time processing efficiency and quickly identify bottlenecks.
Qualifications:Education: * Degree in Computer Science, Data Engineering, or a related technical field.
Experience: * At least 1+ year of experience managing data streams for products in production with multiple data sources. * Experience working with financial systems data (e.g., transactions, user profiles, behavior data) is a plus.
Technical Skills: * Strong proficiency in Python and good knowledge of AWS services (required). * Experience with relational databases like Amazon RDS or Aurora. * Familiarity with AWS SQS FIFO queues for handling and sequencing real-time data. * Proven ability to create and maintain scalable feature preprocessing pipelines. * Expertise in SQL for data manipulation and query optimization. * Familiarity with tools for managing data pipelines and ETL processes (e.g., Apache Airflow, dbt).
Key Traits: * Strong analytical and problem-solving skills. * Clear understanding of production-level data infrastructure and its scalability requirements. * Excellent communication skills (B2+ English), with the ability to convey technical concepts to non-technical stakeholders. * Team-oriented mindset and the ability to thrive in a collaborative, fast-paced environment.
Why Join Us? * Start part-time and scale to full-time based on mutual success. * Contract-based position with competitive and transparent compensation. * Opportunity to work with a talented, globally distributed team on cutting-edge solutions. * Fully remote work with flexible hours (primarily Western European time zone). * Professional development opportunities in a supportive and innovative environment.
If you’re passionate about building scalable and efficient data systems and want to be part of a team shaping the future of fraud prevention, we’d love to hear from you!
