Senior Architect, Databricks

West Monroe•Washington, DC

7d•$183,800 - $244,700•Hybrid

About The Position

West Monroe is seeking a Senior Architect to join our thriving Technology and Experience Practice. This is an excellent opportunity to work with clients developing Big Data strategy and roadmaps with emphasis on Databricks, while gaining exposure to a variety of industries including Healthcare, Financial Services, Insurance, and Utilities.

Requirements

10+ years of professional experience and 3+ years of expeirence with Databricks
8+ years of prior consulting experience
Very strong technical expertise in Databricks, including architecture, performance optimization, Delta Lake, Unity Catalog, workflow orchestration, security, governance, and cloud-native data engineering best practices
Experience architecting and deploying AI/ML or Generative AI solutions within enterprise environments
Hands-on experience with LLM ecosystems and frameworks such as OpenAI, Azure OpenAI, LangChain, Semantic Kernel, MLflow, or Databricks Mosaic AI
Knowledge of Retrieval-Augmented Generation (RAG), vector databases, embeddings, prompt engineering, and AI orchestration patterns
Familiarity with AI governance, model lifecycle management, responsible AI principles, and enterprise security considerations
Experience integrating AI capabilities into data platforms, analytics solutions, or customer-facing applications
Knowledge of standard methodologies, concepts, best practices, and procedures within a Big Data environment
A commitment to inclusion and diversity, and openness to new ideas and perspectives

Nice To Haves

Travel requirements up to 30 to 50%

Responsibilities

Design data flow and processing pipelines for analysis using modern toolsets such as Spark on Scala, Storm, Flume, Sqoop
Design data structures for ingestion and reporting, specific to use case and technology
Provide data management expertise to our clients in evaluating requirements and developing data architecture and performing platform selection and design. Data management includes appropriate structuring, stewardship of data, semantics/syntax of data attributes, coding structures, and mapping schemes
Collaborate with data science and engineering teams to productionize machine learning and Generative AI workloads within modern cloud ecosystems
Establish best practices for AI data readiness, feature engineering, model monitoring, observability, and governance
Lead technical discussions around AI-enabled modernization strategies including semantic layers, vector databases, AI agents, and knowledge retrieval systems
Evaluate emerging AI technologies and recommend fit-for-purpose tooling aligned to client objectives, scalability, security, and compliance requirements
Guide and coach consultants, share best practices, perform code reviews
Coordinate activities with data source application owners to ensure integration with analytics platform and source systems
Ensure that data integrity issues are addressed
Liaise and attend meetings necessary to perform duties and aid business and technical development