About the company
At Databricks, our core principles are at the heart of everything we do; creating a culture of proactiveness and a customer-centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user-friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement.
Responsibilities
- Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning.
- Build and deliver compelling proofs-of-concept and live demos on the Databricks Platform that drive technical wins.
- Own frontline technical relationships with customer engineers, data teams, and technical leads.
- Develop account-level technical strategies in partnership with your Account Executive to grow platform consumption.
- Navigate competitive landscapes by articulating Databricks differentiation through hands-on demonstrations.
- Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community.
Requirements
- 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role.
- Proficient in Python and SQL with demonstrated ability to debug, optimize, and write production-quality code — live coding is a required interview stage.
- Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP).
- Working knowledge of distributed data systems: Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink).
- Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews.
- Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics.
- Strong presentation and demo skills — you will build and present a live solution during the interview.
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience).
Nice to Have
- Databricks certification or experience with the Databricks Platform.
- Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow.
- Background at a data/AI company, cloud provider, or technical consulting firm.