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

Meet the Team

Splunk’s Lakehouse team builds analytics capabilities that help customers search and analyze data wherever it resides. Our work extends the Splunk data platform to connect with data lakes and turn distributed data into actionable insights. We bring an engineering- and product-focused approach to solving problems, working closely with product partners and engineers across teams. Join a collaborative team where you can shape technical solutions, share your expertise, and see your work help customers answer real-world questions.

Your Impact

Own the delivery of features, 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, knowledge sharing, and mentoring colleagues while contributing ideas to the product roadmap.

Minimum Qualifications

• Bachelor’s degree in Computer Science, a related STEM field, or a related discipline with 5+ years of related professional experience; 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.

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Preferred Qualifications

• 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.