Staff Data Engineer, Neonomics

• Proven track record as a Data Engineer in building and managing data platforms, especially in fintech or regulated industries
• Proficient in Python, SQL, and data libraries like Pandas and PySpark
• Experience with containerized workloads and Kubernetes
• Familiarity with cloud environments (Google Cloud is a plus)
• Problem-Solving: Ability to tackle complex data challenges with scalable, efficient solutions

Desirable

• We are looking for a Staff Data Engineer who can shape and build our long-term data platform strategy and help us manage financial data. You’ll work closely with cross-functional teams to design, implement, and maintain a scalable data platform using Python, PySpark, SQL, Kubernetes, and a cloud environment (preferably Google Cloud)
• Data Platform Strategy & Implementation: Develop and implement a long-term strategy for our data platform to handle large-scale financial data
• Data Engineering: Build and maintain data pipelines, design ETL/ELT processes, and optimize data storage for efficient ML and analytics workflows
• Collaboration: Work with product managers, backend engineers, and compliance experts to deliver robust solutions
• Cloud & Infrastructure: Deploy and monitor applications in containerized environments (Kubernetes) and cloud platforms
• Compliance & Security: Ensure best practices for data governance, security, and regulatory compliance are followed