# Solutions Architect

**Company**: Databricks
**Location**: Stockholm
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q18350420

**Apply**: https://job-boards.greenhouse.io/databricks/jobs/8531153002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_102576d4-b00

## Description

Solutions Architect – Data & AI (Presales) at Databricks

As a Solutions Architect, you will combine customer engagement with hands-on technical expertise. You will work closely with customers to understand their challenges and demonstrate how the Databricks platform can solve them.

## Responsibilities

- Partner with Account Executives to drive technical sales cycles and customer outcomes

- Lead customer workshops, discovery sessions, and technical deep-dives across multiple stakeholders

- Build and deliver proof-of-concepts, demos, and solution prototypes using real data

- Translate business requirements into practical, scalable data and AI solutions

- Act as a trusted advisor, while also being able to go hands-on to validate solutions end-to-end

- Work through technical challenges with customers, iterating and resolving issues as they arise

- Contribute reusable assets, patterns, and best practices that accelerate adoption across customers

## Requirements

### Customer-facing mindset

- Experience working with customers in a presales, consulting, or advisory capacity

- Ability to communicate complex topics to both technical and non-technical audiences

- Comfortable leading discussions that connect business goals to technical decisions

### Hands-on technical foundation

- Experience with Python (or similar) and familiarity with distributed data processing and compute and working with large-scale datasets

- Understanding of data pipelines and modern data architectures

- Ability to work practically with data (e.g. building PoCs, exploring datasets, troubleshooting)

- Comfortable reasoning through code, explaining how it works, and adapting it when things don’t behave as expected

### Data & AI understanding

- Familiarity with analytics, data science, or machine learning workflows

- Understanding of how data platforms support AI use cases (e.g. feature pipelines, model training, inference)

- Interest in modern AI capabilities, combined with an understanding of how they operate on real data systems

### Architecture & platform understanding

- Familiarity with cloud platforms and data technologies

- Ability to design solutions that consider scalability, performance, reliability, and data volumes

- Awareness of trade-offs in architecture decisions and ability to adapt designs based on constraints

## Success factors

- Comfortable switching between business dialogue and technical execution

- Building, validating, and iterating on solutions in practice

- Taking ownership of technical challenges and pushing problems forward

- Applying structured thinking in discovery and connecting requirements to scalable technical solutions

- Understanding that AI solutions depend on solid data foundations

- Curious and continuously deepening technical expertise

## Skills

### Required
- Python
- distributed data processing
- data pipelines
- modern data architectures
- analytics
- data science
- machine learning
- cloud platforms
- data technologies

---

Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/databricks/jobs/8531153002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)