Staff Data Platform Software Engineer @ ServiceNow
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Company Overview
ServiceNow, founded in sunny San Diego, California in 2004 by visionary engineer Fred Luddy, is a global market leader. With an intelligent cloud-based platform that connects people, systems, and processes, ServiceNow empowers organizations to work smarter, faster, and better.
Job Overview
The Analytics Team builds and maintains robust data pipelines, semantic layers, and data applications that enable efficient data flow, enhanced accessibility, and insightful analytics. As a Staff Data Platform Software Engineer, you will create and optimize scalable data solutions that drive decision-making across the organization.
Key Responsibilities and Requirements
- Develop complex data pipelines using Java and similar OO languages.
- Work with technologies such as Spark, Trino, and semantic layers from Tableau/Power BI.
- Leverage expertise in relational databases including Oracle, MySQL, PostgreSQL, Snowflake, and Databricks.
- Apply deep understanding of SQL, Unix shell, and modularized software architecture.
- Exhibit technical leadership in project ownership, mentoring, and integration test automation.
Qualifications
Candidates should have over 10 years of experience in Java or comparable object-oriented languages, extensive knowledge in big data frameworks, and hands-on experience in creating declarative data pipelines and robust semantic models.
Additional Information
ServiceNow values flexible work personas and an inclusive hiring approach. Accommodations are available for candidates requiring assistance during the application process. Compliance with export control regulations is required for relevant positions.
Key skills/competency
- Java
- Data Pipelines
- Semantic Layers
- Spark
- Trino
- Data Modeling
- SQL
- Big Data
- Unix Shell
- Technical Leadership
How to Get Hired at ServiceNow
🎯 Tips for Getting Hired
- Customize your resume: Highlight Java, big data, analytics skills.
- Research ServiceNow: Understand their cloud platform and culture.
- Showcase project success: Emphasize complex pipeline projects.
- Prepare for technical questions: Focus on Java, SQL, and data modeling.