Sr. Solutions Engineer - Digital Native Business (Strategic Accounts)

Role overview

As a Senior Solutions Engineer, you will lead technical customer engagements from discovery through solution design, proof of concept, and live demonstration. The role combines hands-on coding, architecture, technical storytelling, and account strategy to help digital-native organizations adopt and expand their use of a data and AI platform. You will work closely with an Account Executive while owning relationships with customer engineers, data teams, and technical decision-makers.

Responsibilities

- Lead technical discovery and design solutions for workloads involving data engineering, analytics, and machine learning. - Build and present working proofs of concept and live demonstrations that address customer needs and support technical wins. - Develop account-level technical strategies that increase platform adoption and usage. - Guide architecture reviews, whiteboarding sessions, and other conversations with customer technical teams. - Explain competitive differentiation through practical, hands-on demonstrations. - Create reusable notebooks, solution accelerators, reference architectures, and other assets for the wider solutions engineering community.

Requirements

- At least four years of experience in data engineering, solutions architecture, technical pre-sales, or hands-on consulting. - Strong Python and SQL skills, including debugging, optimization, and production-quality coding; live coding is part of the interview process. - 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 customer-facing discovery, architecture, and technical design discussions. - Familiarity with data engineering, ETL/ELT, streaming, data science or machine learning, MLOps, or SQL analytics. - Strong presentation and demonstration skills, including the ability to build and present a live solution. - Bachelor’s or master’s degree in computer science, engineering, a quantitative discipline, or equivalent experience.

Nice to have

- Certification or practical experience with the relevant data and AI platform. - Familiarity with Unity Catalog, declarative Spark pipelines, MLflow, or comparable governance and machine-learning tooling. - Experience at a data or AI company, cloud provider, or technical consulting organization.

Benefits and work setup

A published local pay range is $152,300–$209,450 USD. Total compensation may also include performance incentives, equity, and region-specific benefits. The interview process includes recruiter and hiring-manager conversations, design and architecture, live coding, a build-and-present exercise, and reference checks.