Senior Technical Solutions Engineer, Spark

P-993; This role is based in São Paulo and it's a hybrid role; 2-3 days in the office. 

As a Spark Technical Solutions Engineer, you will provide a deep dive technical and consulting
related solutions for the challenging Spark/ML/AI/Delta/Streaming/Lakehouse reported issues
by our customers and resolve any challenges involving the Databricks unified analytics
platform with your highly comprehensive technical and customer communication skills. You
will assist our customers in their Databricks journey and provide them with the guidance,
knowledge, and expertise that they need to realize value and achieve their strategic objectives
using our products.

The Impact You Will Have

• 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, etc.

What we look for:

• 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.

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