Senior Solutions Engineer
Leads customer-facing technical discovery, solution architecture, proofs of concept, and platform demonstrations across data engineering, analytics, and machine learning. Requires at least four years of relevant experience, strong Python and SQL skills, public-cloud implementation experience, and customer presentation expertise.
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.
- Articulate Databricks differentiation through hands-on demonstrations and competitive engagements.
- Contribute reusable notebooks, solution accelerators, and reference architectures.
Requirements
- 4+ years of experience in data engineering, solutions architecture, technical pre-sales, or hands-on consulting.
- Proficiency in Python and SQL, including debugging, optimization, and production-quality coding.
- Experience designing and implementing data solutions on AWS, Azure, or Google Cloud.
- 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-haves
- Databricks certification or Databricks Platform experience.
- Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow.
- Background at a data/AI company, cloud provider, or technical consulting firm.
Interview process
- Recruiter screen
- Hiring manager screen
- Design and architecture interview
- Live coding assessment
- Build, demo, and pitch presentation
- Reference check
Benefits
- Comprehensive benefits and perks, with details varying by region.
Skills
Python, SQL, AWS, Microsoft Azure, GCP, Spark, Delta Lake, Hadoop, Kafka, Apache Flink, ETL, ELT, MLOps, Databricks, MLflow
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