채용
Benefits & Perks
•Annual team offsites
•Health, dental, and vision coverage
•Top Tier compensation with equity
•Remote work flexibility
•Learning and development stipend
•Parental leave program
Required Skills
Python
PyTorch
Airflow
P-1411
Note: this is a hybrid role and requires ~3 days in the office in São Paulo-SP.
Mission
As a Staff Data & AI Technical Solutions Engineer, you will personally drive and mentor others in producing Data & AI technical solutions for any issues reported by customers - including deep diving into production data pipelines, AI workflows, streaming data ingestion, and more. You have deep expertise in Data & AI architectures, having seen a broad set of use cases and successfully maintained complex production environments while adhering to SLA’s. You collaborate effectively with other teams, such as product engineering and customer account teams, to deliver results for customers, especially during critical production downtime situations. You provide customers with the guidance, knowledge, and expertise to build performant architectures and reliable services to achieve their strategic objectives using Databricks’ platform. Reporting to a TSE manager, you are a technical expert within a world-class global support engineering organization, recognized for your leadership, technical depth, and ability to troubleshoot even the most complex customer situations.
The impact you will have:
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Be directly responsible for leading and driving technical solutions for a breadth of complex problems reported by Databricks customers, including escalated and critical scenarios.
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Deep Dive into code-level analysis and systems architecture of customer workloads to address issues related to Databricks products - including Spark core internals, Spark SQL, Delta, DLT, and Model Serving.
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Serve as a customer support advisor - be able to diffuse escalations during incidents directly with customer stakeholders, quickly find mitigations and solutions for advanced use cases, and be strategic at helping prevent future customer issues.
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Help make the Databricks products simpler to use and customer production environments more stable, such as by influencing Engineering and Backline Support teams to identify areas for product improvements.
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Be known as a deep technical expert and leader in the Databricks platform and productionizing systems, and mentor others in those areas to spread your knowledge.
What we look for:
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Minimum of 8 years of experience in designing, building, testing, and maintaining data pipelines. Relevant past Spark experience is mandatory.
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Expertise in SQL databases or data warehouses (such as Oracle, Teradata, SQL Server, MySQL) and ETL technologies (such as Informatica, Data Stage, Talend, Fivetran).
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5 years of hands-on experience in developing two or more Big Data technologies, such as Spark & Hadoop, Lakehouse architecture - such as Delta, Data Ingestion, Data Streaming applications, or ML/AI applications for industry use cases.
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Around 3 years of hands-on experience as a technical lead on a Data & AI Engineering team, serving as the go-to person to resolve critical issues.
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Prior Support or customer-facing experience is not required for this role, but proven ability to influence cross-functionally is, such as with internal stakeholders or engineering teams.
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Preferably: Hands-on experience with public cloud (AWS, Azure, or GCP).
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Technical degree or Bachelor's Degree in Computer Science or related field/experience
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.
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About Databricks

Databricks
Series IDatabricks, Inc. is an American software company based in San Francisco. It was founded in 2013 by the original creators of Apache Spark. It offers a cloud-based platform for data analytics and artificial intelligence.
6,000+
Employees
San Francisco
Headquarters
$43B
Valuation
Reviews
4.2
9 reviews
Work Life Balance
3.5
Compensation
4.7
Culture
4.3
Career
4.5
Management
4.0
86%
Recommend to a Friend
Pros
Working on industry-leading data and AI platform
Excellent compensation with high equity upside
Strong engineering culture with Apache Spark creators
Cons
High intensity work environment with demanding deadlines
Work-life balance can suffer during key releases
Growing pains as company scales rapidly
Salary Ranges
25 data points
Junior/L3
Mid/L4
Staff/L6
Junior/L3 · Data Scientist L3
0 reports
$244,818
total / year
Base
-
Stock
-
Bonus
-
$208,096
$281,540
Interview Experience
9 interviews
Difficulty
3.0
/ 5
Duration
21-35 weeks
Offer Rate
22%
Experience
Positive 22%
Neutral 67%
Negative 11%
Interview Process
1
Application Review
2
Recruiter/Phone Screen
3
Technical Interview/Coding Round
4
System Design Interview
5
Behavioral Interview
6
Final Round/Hiring Manager Interview
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
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