Senior Solutions Engineer
Leads customer-facing technical discovery, solution design, proofs of concept, and demonstrations for data, analytics, and machine-learning workloads on Databricks. Requires 4+ years of relevant experience, strong Python and SQL skills, cloud data-platform expertise, and technical presentation ability.
About the job
Responsibilities
- Lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning.
- Build and deliver proofs of concept and live demonstrations on the Databricks Platform.
- Own technical relationships with customer engineers, data teams, and technical leads.
- Develop account-level technical strategies with Account Executives to grow platform consumption.
- Explain Databricks’ differentiation through hands-on demonstrations in competitive situations.
- Contribute reusable notebooks, solution accelerators, and reference architectures.
Requirements
- 4+ years of experience in data engineering, solutions architecture, technical presales, or hands-on consulting.
- Proficiency in Python and SQL, including debugging, optimization, and production-quality coding.
- Experience designing and implementing data solutions on at least one public cloud platform.
- Working knowledge of distributed data systems such as Apache Spark, Delta Lake, Hadoop, Kafka, or Flink.
- Experience leading technical customer conversations, including discovery, whiteboarding, and architecture reviews.
- Familiarity with data engineering, data science or machine learning, or SQL analytics.
- Strong presentation and demonstration skills.
- 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 or AI company, cloud provider, or technical consulting firm.
Skills
Python, SQL, AWS, Microsoft Azure, GCP, Spark, Delta Lake, Hadoop, Kafka, Flink, Databricks, Unity Catalog, MLflow, MLOps, Data Engineering
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