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Databricks
Senior Manager - Technical Solutions (Spark)
CSQ426R84
Databricks helps data teams solve the world’s toughest problems. As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition Databricks is venture-backed and founded by the original creators of popular open source projects: Apache Spark™, Delta Lake and MLflow.
As a Senior Manager of the Spark Technical Solutions team, you will lead & manage a team of Technical Solution Engineers (Spark) and be responsible for driving deep dive technical solutions for any issues reported by Databricks customers. We expect the manager to resolve 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 realise value and achieve their strategic objectives using our products.
The impact you will have:
- As a manager and member of the leadership team, you will be directly responsible for the management of Technical solution engineers, team leads and operations personnel
- Responsible for directly monitoring, reporting, and driving improvements to team-level metrics and KPIs, acting as an escalation point with customers and internal teams, and optimising and developing support processes and tools
- Responsible for working across multiple cross functional teams that include Engineering, product management, sales and customer success; manage Hiring, mentoring and onboarding new support engineers
- Regularly meet one-on-one with your direct reports, conducting annual reviews and career development discussions throughout the year
- Be a hands on manager to assist the team members in resolving issues related to Spark core internals, Spark SQL, Structured Streaming, Delta, Lakehouse and other databricks runtime features
- Manage and drive best practices guidance around Spark runtime performance and usage of Spark core libraries and APIs for custom-built solutions developed by Databricks customers; contribute in the development of tools/automation initiatives
- Own Engineering JIRA tickets and proactively work to bring quicker resolutions to customer reported issues; participate in creation of knowledge base articles
- 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 10-12 years of experience in designing, building, testing, and maintaining Python/Java/Scala/Spark based applications in a typical project delivery and consulting environments with 4+ years working as a Manager
- 5+ years of hands-on experience in developing and leading 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.
- Big Data / Apache Spark hands on-experience is mandatory
- Hands on experience in the performance tuning/troubleshooting of Hive and Spark based applications at production scale. 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 Data lakes and any SQL-based databases, Data Warehousing/ETL technologies like Informatica, DataStage, Oracle, Teradata, SQL Server, MySQL is preferred
- Hands-on experience with AWS or Azure or GCP is preferred
- Experience in implementing CI/CD, Monitoring/alerting for Production Systems
- Technical lead in design, implementation and support of large scale data and analytics solutions that are highly reliable, flexible, and scalable
- Experience in leading and managing end-to-end projects and have reported and escalated to top levels
- Experience in managing and leading teams in an organisation involving multiple reporting lines
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
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.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
