Staff Data & AI Technical Solutions Engineer

Reposted 14 Days Ago
Be an Early Applicant
São Paulo
In-Office
Senior level
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role
As a Staff Technical Solutions Engineer, you will resolve customer issues related to Apache Spark, provide guidance on best practices, and assist customers in optimizing their use of Databricks products.
Summary Generated by Built In

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: 

  • Be directly responsible for leading and driving technical solutions for a breadth of complex problems reported by Databricks customers, including escalated and critical scenarios.
  • 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.
  • 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.   
  • 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. 
  • 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:  

  • Minimum of 8 years of experience in designing, building, testing, and maintaining data pipelines. Relevant past Spark experience is mandatory.
  • Expertise in SQL databases or data warehouses (such as Oracle, Teradata, SQL Server, MySQL) and ETL technologies (such as Informatica, DataStage, Talend, Fivetran).
  • 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.
  • 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.
  • 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.
  • Preferably: Hands-on experience with public cloud (AWS, Azure, or GCP).
  • 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.

Top Skills

Spark
Artificial Intelligence
AWS
Azure
Data Lakes
Data Science
Elasticsearch
GCP
Hadoop
Java
Kafka
Linux
Machine Learning
Python
Scala
SQL
Streaming
Unix
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The Company
New York, NY
2,200 Employees
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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