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P-1625
Important Notes:
- This is a hybrid role and requires ~3 days in the office in São Paulo-SP. Our office is in Av Faria Lima.
- Please, submit your application and resume in English.
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 Apache 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).
- Bachelor's Degree in Computer Science or related field/experience.
- Mandatory Bilingual Proficiency (English & Portuguese): Full professional fluency in English is required for daily collaboration with US-based internal teams, alongside full professional fluency in Portuguese to directly support our Brazilian customer base.
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
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 click here.
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.
Skills Required
- Minimum 8 years of experience designing, building, testing, and maintaining data pipelines
- Hands-on experience with Apache Spark
- Expertise in SQL databases or data warehouses
- Experience with ETL technologies such as Informatica, DataStage, Talend, or Fivetran
- At least 5 years of hands-on experience developing two or more big data technologies or solutions, including Spark, Hadoop, lakehouse architecture, data ingestion, data streaming, or ML/AI applications
- Approximately 3 years of hands-on experience as a technical lead on a Data and AI Engineering team
- Proven ability to influence cross-functionally with internal stakeholders or engineering teams
- Technical degree or bachelor's degree in Computer Science or a related field, or equivalent experience
- Hands-on experience with AWS, Azure, or Google Cloud Platform
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Healthcare Strength — Healthcare coverage is described as comprehensive, including medical, dental, and vision for employees and dependents, plus dedicated mental-health resources and an EAP. Wellness and gym reimbursements further support wellbeing.
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Equity Value & Accessibility — Equity grants (RSUs/stock options) are highlighted as a major part of compensation and are often viewed as attractive. Occasional tender-offer liquidity and performance bonuses reinforce total rewards.
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Parental & Family Support — Paid parental leave, fertility benefits, and subsidized backup dependent care are emphasized. Family medical leave and caregiver support also feature in the package.
Databricks Insights
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.
