Solutions architect at Databricks Bengaluru, serving as the long-term technical advisor to named strategic enterprise accounts on data and AI.

This full-time Bengaluru role was posted on 16 September 2026. The listing describes a Global Capability Center field engineering role: deeply embedded with named strategic accounts, collaborating with internal sales, product and engineering teams, and helping customers achieve data-driven outcomes on the Databricks platform. Requirements include 12+ years in data engineering, data science, technical architecture or a similar pre-sales/consulting role, and 8+ years hands-on with Big Data and AI technologies including Apache Spark. The listing stresses hands-on architectural depth: able to whiteboard, design and personally build end-to-end solutions, not just advise.

About Databricks

Databricks builds a data and AI platform around the lakehouse architecture, combining data warehousing and data lakes for analytics, data engineering and machine learning. The company was founded by the creators of Apache Spark.

Databricks has a large engineering presence in Bengaluru, with listings spanning platform engineering, monitoring and reliability, and customer-facing engineering roles. Learn more on Databricks's website.

The role in plain terms

The 'not just advise' requirement is the defining line: this is a solutions architect who still builds. Strategic-account SAs at Databricks design GenAI and ML architectures with customer teams, which means your Spark and data engineering depth gets tested, not your slide-making. Experience with Fortune 500-scale accounts across geographies is explicitly preferred, so enterprise polish matters as much as technical depth.

The team and the work

Per the listing, the role sits in a field engineering team focused on strategic accounts, partnering with sales on the commercial motion while owning the technical relationship.

What the employer asks for

These requirements are quoted from the employer's listing, kept in their exact words so eligibility details are not distorted:

12+ years in data engineering, data science, technical architecture, or a similar pre-sales / consulting role.
8+ years hands-on experience with Big Data and AI technologies, including Apache Spark™, data engineering, data science, and modern AI/ML workloads.
Strong hands-on architectural experience — able to whiteboard, design, and personally build end-to-end solutions, not just advise.
Demonstrated experience working with large enterprise or Fortune 500 customers; experience supporting global accounts across multiple geographies strongly preferred.
Experience working with digital-native or SaaS enterprises with mature data and AI practices is a strong plus.
Strong consulting / customer-facing experience working with external clients across a variety of industries.
Coding experience in Python, SQL, Scala, Java, or R.
Experience building distributed data systems at enterprise scale.

Who this role suits

Senior data engineers or architects with 12+ years who want customer-facing strategic work without losing hands-on building. Not for architects who have moved fully into advisory work, or those without Spark and big-data depth.

Practical notes

For strategic SA roles, expect an architecture deep-dive (design a lakehouse or GenAI system for an enterprise scenario) plus account-strategy questions. Hands-on claims get verified, so be ready to discuss real systems you built.

Working at Databricks

Work at Databricks centres on large-scale data systems: query engines, orchestration, observability and the infrastructure that runs customer data and AI workloads.

How to apply

Apply directly on the employer's site: Solutions Architect at Databricks. We found this listing on the Greenhouse public job board (databricks.com), where it was posted on 16 Sep 2026 and was still open when we checked on 30 Oct 2026. Before applying, re-read the employer's own description in full, since eligibility details, deadlines and process steps can change at any time and the employer's page is always the final word. Tailor your resume to the specific requirements above rather than sending a generic one: mirror the skills and tools the listing names where you genuinely have them. A short, specific note on why this team and this problem interest you goes further than a long generic cover letter. Never pay a fee to apply or interview; genuine employers, including this one, do not charge candidates.

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