Staff Software Engineer, Streaming Data

Summary

Join Narvar's team as a Staff Data Engineer to build fraud prevention products and improve the company's platform by designing, developing, and maintaining robust streaming data pipelines.

Requirements

• 8+ years of relevant experience
• Proven experience working with streaming data pipelines, preferably using Apache Beam, Dataflow, or similar technologies
• Extensive experience working with Kafka, Pub/Sub or similar technologies
• Extensive experience with large-scale databases such as Google Bigtable/Cassandra, including building and optimizing APIs to serve data
• Expertise in designing table schemas in Bigtable, following best practices for efficient data access and performance
• Expertise in one of the following programming languages: Java, Golang, or Rust
• Demonstrated experience in a zero-to-one startup environment, with the ability to thrive in a fast-paced, entrepreneurial setting
• Strong ownership mindset with a proactive approach to problem-solving and a commitment to delivering high-quality results
• Proficiency in writing SQL queries for analysis and debugging
• Excellent communication and collaboration skills, with the ability to work effectively in a team-oriented environment

Responsibilities

• Design, develop, and maintain robust streaming data pipelines using technologies like Apache Beam, Dataflow, or similar frameworks
• Architect, implement, and optimize APIs that serve data from large-scale databases such as Google Bigtable
• Design and optimize table schemas in Bigtable, following best practices to ensure efficient data access and performance
• Write efficient, maintainable, and scalable code in one of the following languages: Java, Golang, or Rust
• Demonstrate strong ownership of work by driving projects from concept to production, ensuring high-quality deliverables
• Troubleshoot and resolve data pipeline issues, ensuring high availability and reliability of data services
• Stay updated with the latest industry trends and best practices in data engineering and DevOps
• Collaborate with cross-functional teams to architect scalable data solutions that meet the needs of our rapidly evolving business

Preferred Qualifications

• Prior experience in working in the Fraud/Risk domain
• Experience with cloud platforms such as Google Cloud Platform (GCP), AWS, or Azure
• Familiarity with Devops fundamentals, containerization technologies such as Docker and Kubernetes
• Understanding of data security and privacy best practices