Spark Atse

Mission

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.

Outcomes
- 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 customerʼs 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.
- Provide best practices guidance around Spark runtime performance and usage of

Spark core libraries and APIs for custom-built solutions developed by Databricks

customers.
- Be a true proponent of customer advocacy.
- Contribute in the development of tools/automation initiatives.
- Provide front line support on the third party integrations with Databricks environment.
- Review the Engineering JIRA tickets and proactively intimate the support leadership

team for following up on the action items.
- Manage the assigned spark cases on a daily basis and adhere to committed SLA's.
- Achieving above and beyond expectations of the support organization KPIs.
- Strengthen your AWS/Azure and Databricks platform expertise through continuous

learning and internal training programs.

Competencies
- Min 6 years of experience in designing, building, testing, and maintaining

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
- 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.

“Distributed Big Data Computing” environment.

(ii) Job Description - Lead Spark TSE (L6)

Mission

As a Lead of the Spark Technical Solutions team, you will lead a team of Technical solution

engineers and be responsible for driving deep dive technical solutions for any issues reported

by Databricks customers. We expect the technical lead to resolve the technical challenges

with 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.

Outcomes
- As a Lead and member of the technical solutions team, you will be directly responsible

for leading and driving technical solutions for the problems reported b