Staff Software Engineer, Performance Optimization
2 months ago
Narvar is a leading platform that drives customer loyalty through seamless post-purchase experiences. We empower retailers to retain, engage, and delight customers, fostering long-term relationships and growth.
Job SummaryWe are seeking a highly skilled Staff Software Engineer to join our team. As a key member of our engineering team, you will design, develop, and maintain robust streaming data pipelines using technologies like Apache Beam, Dataflow, or similar frameworks.
Key Responsibilities- Design and implement efficient, scalable, and maintainable data pipelines using Apache Beam, Dataflow, or similar technologies.
- Architect and optimize APIs that serve data from large-scale databases such as Google Bigtable.
- Design and optimize table schemas in Bigtable, following best practices for efficient data access and performance.
- Write high-quality, efficient, and scalable code in one of the following languages: Java, Golang, or Rust.
- Collaborate with cross-functional teams to architect scalable data solutions that meet the needs of our rapidly evolving business.
- Stay updated with the latest industry trends and best practices in data engineering and DevOps.
- Proven experience working with streaming data pipelines, preferably using Apache Beam, Dataflow, 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.
- Prior experience in working in the Fraud/Risk domain.
- Familiarity with DevOps fundamentals and containerization technologies such as Docker and Kubernetes.
- Understanding of data security and privacy best practices.
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