About this role
Complex enterprise data and AI ecosystems often struggle to unify analytics, data engineering, and generative AI into production-ready platforms that deliver measurable business outcomes. Databricks addresses this challenge by embedding expert technical advisors directly within strategic global accounts to guide architecture, platform adoption, and long-term data strategy.
As a Solutions Architect based in Bengaluru, you will act as a trusted technical counselor for Fortune 500 enterprises and global SaaS customers. You will partner closely with internal sales, product, and engineering divisions to design modern Lakehouse architectures, implement proofs of concept, and shape the future of the Databricks Data Intelligence Platform. The ideal candidate combines deep hands-on technical fluency in big data technologies with strong consulting skills and the ability to build durable relationships with enterprise engineering leaders.
What you will do
- Serve as the trusted technical advisor for named strategic accounts by establishing durable relationships with data, AI, and platform engineering leaders.
- Partner with customer data science and ML teams to design GenAI architectures, evaluate build-versus-buy decisions, and deploy production systems on Databricks.
- Collaborate with the sales team to provide hands-on technical leadership that demonstrates how the platform solves business problems across the data lifecycle.
- Consult on modern Lakehouse architectures and execute proofs of concept spanning data engineering, data warehousing, machine learning, and generative AI.
- Work directly with product and engineering teams to relay customer feedback and help drive the core Databricks product roadmap forward.
- Coordinate across regions with fellow Solutions Architects to provide consistent architectural guidance for global customer footprints.
- Promote and support open-source projects including Apache Spark, Delta Lake, MLflow, and Unity Catalog within the developer community.
What you need
- Bring 12 or more years of professional background in data engineering, data science, technical architecture, or relevant pre-sales and consulting roles.
- Possess at least 8 years of hands-on experience working with big data and AI technologies like Apache Spark, data science, and modern machine learning workloads.
- Demonstrate strong architectural capabilities that allow you to whiteboard, design, and personally build end-to-end technical solutions.
- Show documented history of supporting large enterprise or Fortune 500 customers across multiple geographies.
- Write code proficiently in Python, SQL, Scala, Java, or R.
- Build distributed data systems at an enterprise scale.
- Maintain hands-on experience using at least one major public cloud provider such as AWS, Azure, or GCP.
- Remain available to travel for customer meetings within your region and occasionally on an international basis.
Nice to have
- Prior experience working in or with a Global Capability Center model
- Databricks Certification
- Experience working with digital-native or SaaS enterprises with mature data and AI practices
Skills and tech stack
Questions candidates ask
What team will I belong to at Databricks?
You will be part of a Global Capability Center focused Field Engineering team reporting to the Field Engineering Manager. The role involves deep embedding with named strategic accounts while collaborating closely with internal sales, product, and engineering teams.
What kind of travel is expected for this role?
You must be available to travel to customers in your region and occasionally internationally. This travel supports regional field teams and strategic global accounts across different geographies.
What technologies and systems will I work with daily?
You will utilize coding languages like Python, SQL, Scala, Java, or R alongside big data and AI technologies including Apache Spark, Delta Lake, MLflow, and Unity Catalog. Additionally, you will work with major public clouds such as AWS, Azure, or GCP to validate integrations.