Job Summary

The DataPelago Solution Architect will serve as the technical partner to customers throughout the pre-sales and early-adoption journey. Working closely with the DataPelago Account Executive, NetApp AI sales teams, and NetApp Account Executives, this person will identify customer workloads, design potential solutions, lead hands-on technical evaluations, and translate customer requirements back to DataPelago's engineering and product teams.

This role extends beyond traditional demonstrations and standard solution configuration. The Solution Architect will help determine where the technology creates the greatest value, drive proof-of-concept (PoC) execution, establish measurable success criteria, and move early customer interest into a successful technical evaluation and deployment.

The ideal candidate will combine deep technical expertise in modern data architectures and distributed data processing with the agility and ownership needed in a startup environment. The individual will help establish technical practices and field engagement models that can integrate into NetApp as DataPelago matures.

Location: San Jose, California

About DataPelago and NetApp

DataPelago is building a new data-processing platform applying accelerated computing for the AI era. Its technology is designed to accelerate analytics and AI workloads by bringing high-performance compute closer to enterprise data.

Following its acquisition by NetApp, DataPelago combines the ownership, pace, and influence of an early-stage company with NetApp's global customer reach, resources, and enterprise relationships. DataPelago will continue operating with a focused, startup-style model while it builds a scalable business and go-to-market motion.

This is a zero-to-one environment. We are looking for builders who are energized by ambiguity, move quickly, work directly with customers, and take ownership beyond traditional role boundaries. The strongest candidates will ideally bring experience from both early-stage companies and established organizations. They will know how to build with speed while also creating the processes, partnerships, and operating discipline needed to scale successfully within a larger enterprise.

Job Responsibilities

• Partner with DataPelago and NetApp Account Executives to identify and qualify technically compelling customer opportunities.


• Participate in early customer conversations initiated by NetApp sellers and translate initial interest into structured technical discovery.


• Understand customers' existing architectures, performance bottlenecks, operational constraints, and desired outcomes.


• Design and communicate solution approaches using DataPelago technology.


• Develop and deliver technical presentations, demonstrations, workshops, and proof-of-concept plans.


• Work hands-on with customers during technical evaluations and help remove barriers to adoption.


• Translate complex product capabilities into clear technical and business value.


• Collaborate closely with DataPelago engineering and product teams to address customer requirements and provide field feedback.


• Create reusable solution patterns, discovery questions, technical qualification criteria, competitive guidance, and evaluation methodologies.


• Support early production deployments where continuity between pre-sales discovery and customer implementation is important.


• Build the technical content, processes, and relationships required to scale DataPelago through NetApp's broader field organization.

Qualifications & Education

• 12+ years of overall experience


• Strong technical experience in databases, data processing, analytics platforms, cloud architecture, or a related area.


• Hands-on experience with distributed data-processing technologies such as Apache Spark, Flink, Trino, Hadoop, or similar frameworks. Strong Apache Spark experience is particularly desirable.


• Understanding of enterprise data engineering and analytics workloads, including ETL/ELT, data preparation, batch and stream processing, SQL-based analytics, and large-scale data transformation.


• Proficiency in SQL and Python, with experience analyzing workloads, diagnosing performance bottlenecks, and troubleshooting distributed data-processing environments.


• Familiarity with modern data architectures and platforms, including data lakes, lakehouse, cloud object storage, Databricks, Snowflake, and major cloud providers such as AWS, Azure, or Google Cloud.


• Experience in a customer-facing technical role such as Solution Architect, Sales Engineer, Field Architect, consultant, or customer-facing engineer.


• Ideally, experience in both an early-stage technology company and a larger enterprise organization.


• Experience collaborating with enterprise Account Executives and field technical teams.


• Ability to evaluate early customer leads and assess technical fit, use-case clarity, and readiness for deeper engagement.


• Experience supporting complex evaluations, proofs of concept, or early production deployments.


• Strong communication skills with technical practitioners, architects, business stakeholders, and executives.