Senior Data & AI Solutions Architect — Client-Facing

Databricks Inc.

New York (NY)

On-site

USD 182,000 - 250,208

Full time

14 days+

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Job summary

Databricks is seeking a Forward Deployed Engineer to lead production-grade data/AI solutions for customers in the New York area. You will own the architecture, drive design decisions, and deliver end-to-end systems spanning data engineering, AI, and application development.

Ideal candidates have 6+ years in data/analytics or software engineering, cloud experience (AWS/Azure/GCP), and a strong Spark background, with travel to clients about 20% of the time. Certification in Databricks is a plus.

Qualifications

6+ years experience in data engineering, data platforms & analytics, or software engineering.
Working knowledge of two or more Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals.
Familiarity with CI/CD for production deployments.
Working knowledge of MLOps, ML/AI models and AI APIs.
Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.
Documentation and white-boarding skills.
Experience working with enterprise clients and managing conflicts across a broad stakeholder range
Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
Travel to customers 20% of the time
Databricks Certification

Responsibilities

Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer
Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.