Staff Technical Solutions Engineer - Spark

Posted 5 Days Ago
Be an Early Applicant
San Francisco, CA
120K-212K Annually
Senior level
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role
Provide advanced technical solutions for Spark and related technologies, troubleshoot issues, and guide customers in leveraging the Databricks platform.
Summary Generated by Built In

CSQ126R234

As a Staff Technical Solutions Engineer, you will provide advanced technical solutions and consulting for complex Spark, ML/AI, Delta, Streaming, and Lakehouse-related challenges reported by our customers. You will leverage your deep technical and client-facing skills to resolve issues involving the Databricks Data Intelligence Platform. Your expertise will guide customers on their Databricks journey, helping them achieve value and their strategic goals using our products.

The impact you will have: 

  • Perform deep technical analysis and troubleshooting of Spark issues using UI metrics, DAG, Event Logs, and logs related to job performance and failures.
  • Troubleshoot, resolve and conduct code-level analysis of Spark core internal, Spark SQL, Structured Streaming, Delta Lake, and other Databricks runtime features.
  • Assist customers in reproducing Spark issues and provide solutions in areas such as SQL, Delta, memory management, performance tuning, streaming, data science, and data integration.
  • Act as a designated solutions engineer for strategic customers, addressing their Spark and cloud-related challenges daily.
  • Collaborate with Account Executives, Customer Success Engineers, and Resident Solution Architects to align customer needs with best practices and solutions.
  • Participate in live troubleshooting sessions via screen sharing, actively engaging with team members and customers to resolve major Spark issues.
  • Contribute to internal knowledge bases, wikis, and technical documentation to support both customers and internal teams.
  • Work closely with Engineering and Backline Support teams to escalate and resolve product defects efficiently.
  • Participate in on-call rotations, driving escalations during Databricks runtime outages and ensuring operational support for critical customer issues.

What we look for:

  • 6+ years of hands-on experience in big data technologies, including Spark, Hadoop, ML, AI, Streaming, Kafka, and data science at a production scale.
  • Expert-level experience in Spark performance tuning and troubleshooting.
  • Strong understanding of JVM memory management, garbage collection, and heap/thread dump analysis.
  • Hands-on experience with SQL-based databases and ETL/data warehousing technologies like Informatica, DataStage, Oracle, Teradata, SQL Server, MySQL, and SCD-type use cases.
  • Experience with cloud services such as AWS, Azure, or GCP.
  • Deep understanding of distributed computing principles and best practices.
  • A Bachelor’s degree in Computer Science or a related field, or equivalent practical experience, is required.

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks utilizes the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.


Zone 1 Pay Range

$120,000$212,300 USD

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.

Top Skills

AI
AWS
Azure
Databricks
Datastage
Delta
ETL
GCP
Hadoop
Informatica
Kafka
Ml
MySQL
Oracle
Spark
SQL
SQL Server
Streaming
Teradata
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The Company
New York, NY
2,200 Employees
On-site Workplace
Year Founded: 2013

What We Do

As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.

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