Solutions Architect
Databricks
Pune, IndiaPosted 1 month ago
Skill Required
Field Engineering - OtherMachine LearningData WarehousingEngineeringDatabricksbuildingEmbedded CPythonMLflowdesignScalaSparkAzureUnityCloudGenerative AIJavaSQLAWSGCPAI
Key highlights
- Job requisition code: FEQ327R324
- Requires a minimum of 12+ years of experience in data engineering, data science, technical architecture, or a similar pre-sales/consulting role.
- Requires a minimum of 8+ years of hands-on experience with Big Data and AI technologies, including Apache Spark.
- Preferred qualifications include Databricks Certification and prior experience working in or with a Global Capability Center (GCC) model.
- Role requires availability to travel to customers in your region and occasionally internationally.
- Employer may decline an applicant if unable to obtain a U.S. government license for access to export-controlled technology required for the role.
Role overview
This is a Solutions Architect role within Databricks' Global Capability Center (GCC) focused Field Engineering team, where you will work with the world's most sophisticated Data and AI teams, including Fortune 500 enterprises and global AI-forward SaaS customers, as a trusted long-term technical advisor for named strategic accounts. You will collaborate with internal sales, product, and engineering teams to help customers achieve tangible data-driven outcomes using the Databricks Data Intelligence Platform across data engineering, analytics, AI, and data science use cases, reporting directly to the Field Engineering Manager.
Responsibilities
- Serve as the trusted technical advisor for one or more named strategic accounts, building deep, durable relationships with their data, AI/ML, and platform engineering leaders, and earning a seat at the table for their most important architectural decisions.
- Shape and drive customer AI strategy by partnering with their data science, ML, and AI platform teams to design GenAI and ML architectures, evaluate build-vs-buy decisions, and turn AI ambitions into production systems deployed on Databricks.
- Partner with sales teams to provide hands-on technical leadership to help large enterprise customers understand how Databricks can solve their business problems across the full data and AI lifecycle.
- Consult on modern Lakehouse architectures and implement proofs of concept for strategic projects spanning data engineering, data warehousing, machine learning, and GenAI, including validating integrations with cloud services, in-house tools, and third-party applications.
- Work with sales teams to develop your book of business, define account strategies, and execute those strategies to help customers and prospects solve their business problems with Databricks.
- Collaborate cross-region with fellow Solutions Architects, account teams, and regional field teams across geographies to support customers with consistent architectural guidance across their international footprint.
- Collaborate with internal sales, product, and engineering teams to drive the Databricks roadmap forward, and work with the broader customer-facing team to develop architectures and solutions using the Databricks platform.
- Guide customers through the competitive landscape, platform best practices, and implementation processes, and develop technical champions within customer organizations.
- Become an expert in, promote, and recruit contributors for Databricks-inspired open-source projects (Apache Spark, Delta Lake, MLflow, Unity Catalog) across the developer community.
Requirements
- 12+ years of experience in data engineering, data science, technical architecture, or a similar pre-sales/consulting role.
- 8+ years of 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, including the ability to whiteboard, design, and personally build end-to-end solutions, not just advise.
- Demonstrated experience working with large enterprise or Fortune 500 customers.
- 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.
- Hands-on experience with at least one major public cloud (AWS, Azure, or GCP).
- Availability to travel to customers in your region and occasionally internationally.
Nice to have
- Experience supporting global accounts across multiple geographies.
- Experience working with digital-native or SaaS enterprises with mature data and AI practices.
- Prior experience working in or with a Global Capability Center (GCC) model.
- Databricks Certification.
Benefits
- At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Additional details
- Job requisition code: FEQ327R324
- Databricks is the Data and AI company, with more than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — relying on its Data + AI Platform. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog.
- Databricks is committed to fostering a diverse and inclusive culture where everyone can excel, with inclusive hiring practices that meet equal employment opportunity standards. Applicants are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
- If access to export-controlled technology or source code is required for performance of job duties, it is within the Employer's discretion whether to apply for a U.S. government license for such positions, and the Employer may decline to proceed with an applicant on this basis alone.