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 Data bricks
unified analytics platform with your highly comprehensive technical and customer
communication skills. You will assist our customers in their Data bricks journey and
provide them with the guidance, knowledge, and expertise that they need to realize
value and achieve their strategic objectives using our products.
Responsibilities:
● 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 data bricks 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
data bricks 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 Data bricks 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 Data bricks
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 Data bricks platform expertise through
continuous learning and internal training programs.
Competencies
● 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.