Job Summary

Meet the Team The Webex Engineering Analytics team is responsible for developing and operating pipelines for Big Data Analytics built on state-of-the-art big data technologies that both solve complex data driven development problems for Webex engineering and enable critical business insights for Webex product.

We are looking for a hands-on Software Engineer to join a high-impact data engineering and analytics team with a focus on developing data products and features by leveraging state-of-the-art big data technologies.

Responsibilities

- Build and operate Kafka-based streaming applications, including ingestion, filtering, enrichment, and replication use cases.

- Develop data processing jobs using Apache Spark and/or Apache Flink, following established patterns and platform guidelines.

- Build high-performant, highly scalable, complex, and distributed systems - end to end.

- Share technical solutions and product ideas with the broader team through design review, code review, proof-of-concepts, and show-and-tell sessions.

- Participate and contribute ideas to our technology, algorithms, and products.

- Work closely with development, test, and various cross-technology teams to design development strategies and plans, followed by designing and writing code reflecting product requirements and functionality.

Education

- M.Tech/M.E. in Computer Science, Information Technology,



or a related field; or B.Tech/B.E. in a relevant discipline with at least 2 years of relevant professional experience.

Required Technical Skills

- Solid foundation in data structures, algorithms and object-oriented design

- Adept in using AI tools like Copilot, Cursor, Codex, etc., in design/development and testing.

- Strong experience in Java, Scala, Golang or other contemporary programming languages/technologies.

- Strong SQL skills and understanding of data modeling for analytical workloads

Preferred Skills (Nice to have)

- Experience in building large, asynchronous task systems, scalable distributed systems with a good understanding of microservices architecture.

- Experience working with Kafka and scaling for high volume workloads.

- Practical experience with Apache Spark and Apache Flink.

- Practical experience with query engines like Trino/Presto.

- Hands-on experience with analytics stores like Apache Pinot/Iceberg for low-latency analytical queries.

- Experience with Docker or other configuration management tools.

- Experience with cloud stacks like AWS etc

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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