Cisco

Software Engineer (Java/Scala), Lakehouse Team - Splunk

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NieokreśloneHybryda·KrakówFull-time

#461307·Dodano 26 dni temu·38

Źródło: Cisco

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Tech Stack / Keywords

Java Scala AWS Azure Terraform CloudFormation ARM templates CI/CD Apache Spark Databricks

Podsumowanie oferty

On Splunk’s Lakehouse team, you’ll extend federated query and data lake capabilities so customers can search and analyze data wherever it resides. You’ll deliver features across design, implementation, and release, building distributed systems with Java or Scala.

Wymagania

Bachelor’s degree in Computer Science, a related STEM field, or a related discipline with 5+ years of related professional experience; a master’s degree in one of these fields with 3+ years of related professional experience; or a PhD in one of these fields with no prior professional experience required.
Experience developing backend software in Java or Scala.
Experience designing and implementing distributed systems using object-oriented or functional programming practices.
Experience developing or deploying applications on AWS or Azure, and using infrastructure-as-code tools such as Terraform, CloudFormation, or ARM templates.
Experience writing automated tests and working with version control and CI/CD pipelines.

Nice to have:

Experience with Apache Spark, Databricks, or similar technologies for processing large volumes of data.
Knowledge of database or query engine internals, such as query planning, execution strategies, indexing, or query optimization.
Experience deploying and operating services using container orchestration platforms.
Experience troubleshooting production services, conducting root cause analysis, and implementing reliability improvements.
Experience mentoring engineers, providing code review feedback, and communicating technical decisions across teams.

Obowiązki

Own feature delivery from technical design through implementation and release to extend Splunk’s federated query and data lake capabilities.
Build secure, maintainable distributed systems with automated tests and technical documentation to support reliable, high-performance data processing.
Investigate and resolve complex issues during development and in production, using root cause analysis to improve reliability and the customer experience.
Collaborate with engineering and product partners to refine requirements, evaluate ideas through prototypes, and communicate delivery progress and technical tradeoffs.
Strengthen engineering practices through code reviews and knowledge sharing, mentor colleagues, and contribute ideas to the product roadmap.

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