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Strider TechnologiesSolutions Engineer – Japan
Solutions Engineer at Strider Technologies driving revenue growth through consultative expertise. Engaging clients and collaborating with sales for technical integration of services.
About the role
- Performing initial level analysis and troubleshooting issues in Spark using Spark UI metrics, DAG, Event Logs for various customer reported job slowness issues.
- Troubleshoot, resolve and suggest deep code-level analysis of Spark to address customer issues related to Spark core internals, Spark SQL, Structured Streaming, Delta, Lakehouse and other databricks runtime features.
- Assist the customers in setting up reproducible spark problems with solutions in the areas of Spark SQL, Delta, Memory Management, Performance tuning, Streaming, Data Science, Data Integration areas in Spark.
- Participate in the Designated Solutions Engineer program and drive one or two of strategic customer’s day to day Spark and Cloud issues.
- Plan and coordinate with Account Executives, Customer Success Engineers and Resident Solution Architects for coordinating the customer issues and best practices guidelines.
- Participate in screen sharing meetings, answering slack channel conversations with our internal stakeholders and customers, helping in driving the major spark issues at an individual contributor level.
- Build an internal wiki, knowledge base with technical documentation, manuals for the support team and for the customers. Participate in the creation and maintenance of company documentation and knowledge base articles.
- Coordinate with Engineering and Backline Support teams to provide assistance in identifying, reporting product defects.
- Participate in weekend and weekday on-call rotation and run escalations during databricks runtime outages, incident situations, ability to multitask and plan day 2 day activities and provide escalated level of support for critical customer operational issues.
Requirements
- Min 6 years of experience in designing, building, testing, and maintaining Python/Java/Scala based applications in typical project delivery and consulting environments.
- 3 years of hands-on experience in developing any two or more of the Big Data, Hadoop, Spark,Machine Learning, Artificial Intelligence, Streaming, Kafka, Data Science, ElasticSearch related industry use cases at the production scale. Spark experience is mandatory.
- Hands on experience in the performance tuning/troubleshooting of Hive and Spark based applications at production scale.
- Proven and real time experience in JVM and Memory Management techniques such as Garbage collections, Heap/Thread Dump Analysis is preferred.
- Working and hands-on experience with any SQL-based databases, Data Warehousing/ETL technologies like Informatica, DataStage, Oracle, Teradata, SQL Server, MySQL and SCD type use cases is preferred.
- Hands-on experience with AWS or Azure or GCP is preferred
- Excellent written and oral communication skills
- Linux/Unix administration skills is a plus
- Working knowledge in Data Lakes and preferably on the SCD types use cases at production scale.
- Demonstrated analytical and problem-solving skills, particularly those that apply to a “Distributed Big Data Computing” environment.
Benefits
- At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.
- For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks
- Hybrid role — 2-3 days in the office
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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