Resident Solutions Architect-HCLS
Senior forward-deployed engineer who designs and productionizes customer data, AI, and application solutions on Databricks. The role owns architecture and delivery while partnering closely with enterprise stakeholders and requires 6+ years of relevant engineering experience.
About the job
Responsibilities
- Lead customer technical projects delivering production-grade data, AI, and application systems.
- Design and build reference architectures, custom applications, data ingestion pipelines, and ML/AI model integrations.
- Guide strategic customers through end-to-end design, implementation, deployment, evaluation, and adoption of Databricks solutions.
- Own architecture and design decisions, ensuring solutions are secure, scalable, performant, and aligned with customer needs and Databricks best practices.
- Collaborate with Databricks technical teams, project managers, architects, customer teams, engineering, product, developer relations, and customer support.
- Embed with customer teams and engage stakeholders ranging from technical individual contributors to executives.
- Scope technical delivery work, manage project scope and timelines, and deliver measurable outcomes.
- Train customers, document solutions, whiteboard architectures, and translate complex concepts into actionable implementations.
- Provide product and implementation feedback and help resolve engagement-specific issues.
- Contribute reusable accelerators, frameworks, and best practices.
- Travel to customers approximately 20% of the time.
Requirements
- 6+ years of experience in data engineering, data platforms and analytics, or software engineering.
- Proficiency in at least one of Python, Scala, JavaScript, or TypeScript, with experience using modern frameworks.
- Working knowledge of at least two cloud ecosystems among AWS, Azure, and Google Cloud, with expertise in at least one.
- Deep experience with distributed computing using 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.
- Experience designing and deploying performant, production-grade end-to-end data architectures and applications combining data pipelines, ML/AI models, and user-facing interfaces.
- Experience delivering technical projects for enterprise clients and managing stakeholders and conflicts.
- Strong documentation and whiteboarding skills.
- Adaptability, curiosity, customer empathy, and eagerness to learn technologies supporting Databricks-based deployments and integrations.
Preferred
- Databricks Certification.
Skills
Python, Scala, JavaScript, TypeScript, AWS, Microsoft Azure, GCP, Spark, CI/CD, MLOps, Machine Learning, Ai Apis, Data Pipelines, Databricks, Distributed Computing
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