Staff Data Engineering (Kafka, Data Streaming)

Are you ready to combine your talent for crafting solid data systems and enthusiasm for cutting-edge technology to harness the power of data at Bazaarvoice?  We’re looking for a strong database engineer who thrives on building large-scale, robust, distributed data systems and pipelines, who understands the importance of good software engineering practices to get it done.  If you’re excited about shaping the future of data at Bazaarvoice, come join us.

As a key member of the Data Operations team, you’ll be tasked with designing, building, and supporting large-scale, distributed data systems that drive our organization’s data infrastructure forward, and power our products and services. Your responsibilities will include managing RDS databases, developing data pipelines, optimizing data storage and retrieval processes, and ensuring the reliability and scalability of our data architecture. You’ll collaborate closely with cross-functional teams to understand data requirements, implement solutions, and troubleshoot issues as they arise. You’ll also play a pivotal role in advocating for and implementing software engineering best practices to ensure the efficiency, maintainability, and robustness of our data systems. This role offers an exciting opportunity to work on cutting-edge technology and contribute to shaping the future of data-driven decision making within our organization.

Identify, analyze, and resolve complex performance and scalability issues

Deeply analyze execution plans, indexing strategies, concurrency, locking, and resource utilization

Design and implement durable performance improvements across queries, schemas, and workloads

Build automation and tooling to detect, diagnose, and remediate database performance issues

Partner with application and platform teams to improve database access patterns and system design

Establish, document, and enforce database performance best practices

Clearly explain complex technical concepts and trade-offs to both technical and non-technical audiences

Candidates must demonstrate expert-level (“can teach a class”) knowledge in all the following:Core Apache Kafka architecture, Amazon MSK, and pub/sub ecosystems. Any Stream Processing & Real-Time Analytics, good to have Apache Flink, Kafka Streams, Spark Streaming, and streaming lakehouses.Experience on Transactional ( PostgreSQL, MySQL, Aurora etc.,) Analytical (Redshift, Iceberg etc.,) Designing and supporting database-backed, event driven application/architecture APIsBuilding automation and tooling to support database performance and reliabilityInfrastructure as Code using TerraformLeveraging AI to automatically identify bottlenecksCloud platforms: AWS, including managed database servicesCI/CD pipelines and deployment automationCapacity planning, workload modeling, and cost optimization