Senior Solutions Engineer

The Role

As a Senior Solutions Engineer, you will independently lead technical engagements with customers, owning discovery, solution design, demonstrations, and proofs of concept. You will combine hands-on technical expertise with strong communication and business acumen to help customers adopt Databricks and achieve measurable outcomes.

The Impact You Will Have

• Lead technical discovery and solution design for workloads spanning data engineering, analytics, machine learning, and AI.
• Build and deliver compelling demonstrations and proofs of concept using the Databricks Plaƞorm.
• Own relationships with customer engineers, data teams, technical leaders, and executives.
• Translate complex technical capabilities into clear business value and measurable outcomes.
• Develop account-level technical strategies in partnership with the Account Executive.
• Guide architecture decisions and help customers integrate Databricks with cloud, open-source, and third-party technologies.
• Navigate competitive evaluations and clearly articulate Databricks’ technical and business differentiation.
• Create reusable notebooks, solution accelerators, reference architectures, and technical enablement materials.
• Contribute to workshops, seminars, meetups, and the broader technical community.

What We Look For

• 3+ years of experience in data engineering, solutions architecture, technical pre-sales, consulting, or a related hands-on technical role.
• Hands-on experience designing and implementing data soluƟons on AWS, Azure, or GCP.
• Proficiency in Python, SQL, Scala, Java, or another relevant programming language.
• Experience with one or more areas such as data engineering, ETL/ELT, streaming, data warehousing, machine learning, MLOps, or generative AI.
• Experience leading technical discovery, whiteboarding, architecture reviews, and customer presentations.
• Strong presentation, storytelling, and live demonstration skills.
• Ability to communicate effectively with both technical and non-technical audiences.
• Bachelor’s or master’s degree in computer science, engineering, mathematics, or a related discipline—or equivalent practical experience.

Nice to Have

• Databricks certification or hands-on experience with the Databricks Plaƞorm.
• Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, MLflow, Apache Spark, Delta Lake, or related technologies.
• Background with a data or AI company, cloud provider, or technical consulting firm.
• Experience supporting enterprise or strategic customer accounts.