2 months ago

Solutions Architect - Field Engineering (GCC)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Senior Solutions Architect within a Global Capability Center Field Engineering team, embedded with named strategic accounts to design and implement end-to-end Data Intelligence Platform architectures. You will act as a trusted technical advisor across data engineering, analytics and AI/ML workloads, collaborate with sales and product teams, and drive GenAI/ML initiatives in large enterprise environments.

Location: Bengaluru, Delhi

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Sr. Manager level

Key Responsibilities

•Be 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
•Help shape and drive your customer's AI strategy—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 the sales team and provide hands-on technical leadership to help large enterprise customers understand how Databricks can help 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, GenAI— including validating integrations with cloud services, in-house tools, and third-party applications
•Work directly with the sales team to develop your book of business, define account strategies, and execute those strategies to help your customers and prospects solve their business problems with Databricks

Key Requirements

•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
•Coding experience in Python, SQL, Scala, Java, or R

Experience:12+ yearsData engineeringAIBig DataEnterprise

Skills:CommunicationLeadershipStakeholder managementPresentationProblem-solving

Languages:English

Tech Stack:PythonSQLScalaJavaRApache SparkDelta LakeMLflowUnity CatalogAWSAzureGCP

Company Brief

Databricks

Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn

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Databricks

2 months ago

Solutions Architect - Field Engineering (GCC)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Bengaluru, Delhi

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Sr. Manager level

Key Responsibilities

•Be 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
•Help shape and drive your customer's AI strategy—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 the sales team and provide hands-on technical leadership to help large enterprise customers understand how Databricks can help 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, GenAI— including validating integrations with cloud services, in-house tools, and third-party applications
•Work directly with the sales team to develop your book of business, define account strategies, and execute those strategies to help your customers and prospects solve their business problems with Databricks

Key Requirements

•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
•Coding experience in Python, SQL, Scala, Java, or R

Experience:12+ yearsData engineeringAIBig DataEnterprise

Skills:CommunicationLeadershipStakeholder managementPresentationProblem-solving

Languages:English

Tech Stack:PythonSQLScalaJavaRApache SparkDelta LakeMLflowUnity CatalogAWSAzureGCP

Company Brief

Databricks

Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn