CSQ127R52
MissionThe Director - Support Engineering (Data & AI) will be responsible for building and leading a regional team of technical experts in Brazil, focused on resolving highly complex and long-running support cases raised by Databricks customers. This leader will oversee all Support Engineering operations during AMER/LATAM business hours with close alignment to global teams and will ensure 24x7 support coverage through coordination with other regions.
Key Outcomes- Build and manage a high-performing regional team of Spark, ML, and AI Technical Solution Engineers in São Paulo (or another major Brazil hub).
- Hire, retain, and develop top talent, building a diverse, world-class support engineering organization.
- Coach and mentor regional support managers and future leaders, while driving structured training, technical workshops, and knowledge-sharing initiatives.
- Define and track quarterly goals for team growth, individual development, and overall performance excellence.
- Partner with Engineering and Product teams to improve product supportability by embedding diagnostics, observability, and support-first practices into design and delivery.
- Lead and resolve escalations during LATAM business hours, ensuring cross-functional collaboration with Engineering, Field, and Global Support teams.
- Act as a player-coach – provide technical leadership (deep dives, debugging, RCA) while scaling organizational processes, tools, and guidelines.
- Drive root cause analysis (RCA) and developer-owned quality practices, ensuring issues are permanently fixed, testing and instrumentation are embedded in the lifecycle, and releases are reliable without reliance on “hero fixes.”
- Build strong engineering-support partnerships by aligning roadmaps, sharing visibility into changes, and implementing joint mechanisms (on-call rotations, incident reviews, escalation playbooks) to improve case routing and resolution speed.
- Lead support tooling and automation initiatives (e.g., log parsers, JVM/heap/thread dump analyzers, AI-assisted triage) to accelerate diagnosis and reduce time-to-resolution.
- Collaborate with Field engineering, Sales and Customer Success teams to address account-level concerns and strengthen adoption of the Databricks platform.
- Demonstrate strong ownership, collaboration, and communication skills to build trust with customers and internal stakeholders.
- Participate in global on-call rotations for critical support escalations.
- Proven people leadership experience: at least 2+ years as a manager of managers.
- 12+ years in the IT industry, with a strong background in Software Engineering, SaaS Support, Data Engineering, or Cloud Platforms.
- Experience leading large teams (50+ employees) in technical support, engineering, or big data consulting.
- Hands-on experience in at least two of the following at production scale:
- Big Data (Spark, Hadoop, Kafka)
- Machine Learning / Artificial Intelligence projects
- Data Science / Streaming use cases
- Spark expertise is a big advantage.
- Strong background in customer-facing support leadership roles.
- Excellent troubleshooting skills across distributed systems.
- Fluent in English and Portuguese (Spanish a plus).
- Strong ownership mindset with the ability to thrive in a fast-paced, startup-like environment.
- Bachelor’s/Master’s in Computer Science or equivalent technical field.
- Strong Java/Scala development, OOP, and distributed systems debugging (JVM, GC, Linux).
- Proficiency in data structures, algorithms, and performance optimization.
- Hands-on with Spark (PySpark, Scala, SQL, Streaming, Performance Tuning, Architecture).
- Experience in data pipeline development & production deployments (Databricks, EMR, On-Prem).
- ML/AI project development and deployment at scale.
- Familiarity with Big Data ecosystems (Hadoop, Hive, Kafka) and major cloud platforms (AWS, Azure, GCP).
- Knowledge of scalable system design, CI/CD practices, and modern DevOps tooling
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
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.
