About the company
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.
Responsibilities
- Own the end-to-end technical strategy for your accounts, from discovery through production deployment and consumption growth
- Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering and real-time analytics
- Serve as a trusted technical advisor to customer architects, engineering leads, and Directors
- Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions
- Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain
- Orchestrate cross-functional resources (DSAs, SAs, Partners) to deliver comprehensive solutions for complex customer needs
- Influence product direction by providing structured feedback on customer requirements and competitive gaps
Requirements
- 6+ years in solutions architecture, technical pre-sales, or a senior hands-on technical role in data and software engineering, data applications engineering, or data warehousing & migration
- Deep hands-on experience with Apache Spark™ ecosystem (Spark Core, Spark SQL, Spark Streaming), message queues (e.g., Kafka), batch ingestion, performance tuning, and troubleshooting complex Spark workloads
- Experience building or supporting data-driven use cases, predictive analytics pipelines, or customer analytics platforms
- Experience migrating EDW workloads (e.g., legacy SQL, Redshift, Snowflake, Synapse, EMR) across OLAP/OLTP systems; advanced query tuning, governance, and MPP debugging
- Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills
- Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms
- Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations)
- Proven ability to lead architecture discussions with senior technical stakeholders — whiteboarding, design reviews, and trade-off analysis
- Experience with production deployments on public cloud (AWS, Azure, or GCP), including infrastructure, security, and governance considerations
- Track record of driving platform adoption and consumption growth within accounts
- Excellent communication skills — able to translate complex architectures into business value for both technical and executive audiences
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)
- Willingness to travel up to 30% as needed
Conditions
- Pay range transparency: $180,000 — $247,500 USD
- Total compensation package may include eligibility for annual performance bonus, equity, and benefits
- Comprehensive benefits and perks