Staff Technical Solutions Engineer, Data & AI
Salary not listed • Sao Paulo, Brazil • Full-time
Posted 3d ago
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
As a Staff Data & AI Technical Solutions Engineer, you will be responsible for driving and mentoring others in producing Data & AI technical solutions for customer-reported issues. This involves deep dives into production data pipelines, AI workflows, and streaming data ingestion. You will leverage your deep expertise in Data & AI architectures to maintain complex production environments and adhere to SLAs. Collaboration with product engineering and customer account teams is key to delivering results, especially during critical production downtime. You will provide customers with guidance and expertise to build performant architectures and reliable services using Databricks' platform, acting as a technical expert within a global support engineering organization.
Responsibilities
- Lead and drive technical solutions for complex customer problems, including escalated and critical scenarios.
- Perform code-level analysis and systems architecture deep dives to address issues related to Databricks products (Spark core, Spark SQL, Delta, DLT, Model Serving).
- Act as a customer support advisor, diffusing escalations, finding mitigations for advanced use cases, and preventing future customer issues.
- Influence Engineering and Backline Support teams to identify product improvements and enhance stability of customer production environments.
- Serve as a deep technical expert and leader in the Databricks platform and productionizing systems, mentoring others.
Requirements
- Minimum of 8 years of experience in designing, building, testing, and maintaining data pipelines.
- Mandatory relevant past Spark experience.
- Expertise in SQL databases or data warehouses (e.g., Oracle, Teradata, SQL Server, MySQL).
- Expertise in ETL technologies (e.g., Informatica, DataStage, Talend, Fivetran).
- 5 years of hands-on experience developing two or more Big Data technologies (e.g., Spark & Hadoop, Lakehouse architecture, Data Ingestion, Data Streaming, ML/AI applications).
- Around 3 years of hands-on experience as a technical lead on a Data & AI Engineering team.
- Proven ability to influence cross-functionally 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.