Overview Senior Architect at West Monroe leads data and AI modernization initiatives within the Technology and Experience Practice. You will design scalable data pipelines and architectures for diverse industries, and guide AI/ML and Generative AI workloads in modern cloud environments. You'll drive data governance, semantic layers, and AI readiness while collaborating with cross-functional teams to deliver measurable client value. This role offers hands-on work with Databricks and emerging AI tooling at scale, with a strong focus on impact and governance.
Compensation / Benefits- medical, dental, vision, and basic life insurance
- 401(k) plan
- employee stock ownership program
- annual bonuses
- unlimited flexible time off
- ten paid holidays per year
Responsibilities- Design data flow and processing pipelines for analysis using Spark on Scala, Storm, Flume, Sqoop
- Create data structures for ingestion and reporting tailored to use case and tech
- Provide data management expertise across requirements, architecture, platform selection and design
- Oversee data governance, semantics, syntax, coding structures, and mapping schemes
- Collaborate with data science and engineering to productionize ML and Generative AI workloads in cloud
- Establish best practices for AI data readiness, feature engineering, model monitoring, observability, governance
- Lead discussions on AI-enabled modernization strategies including semantic layers, vector databases, AI agents, and knowledge retrieval
- Evaluate emerging AI technologies and recommend fit-for-purpose tooling
- Guide and coach consultants, perform code reviews, and share best practices
- Coordinate with data source owners to ensure analytics platform and source systems integration
- Ensure data integrity across platforms
- Liaise in meetings to support business and technical development
Key requirements- 10+ years of professional experience
- 3+ years of experience with Databricks
- 8+ years of consulting experience
- Strong Databricks expertise: architecture, Delta Lake, Unity Catalog, orchestration, security, governance, cloud-native data engineering
- Experience architecting and deploying AI/ML or Generative AI in enterprise environments
- Hands-on with LLM ecosystems and frameworks (OpenAI, Azure OpenAI, LangChain, Semantic Kernel, MLflow, Databricks Mosaic AI)
- Knowledge of Retrieval-Augmented Generation (RAG), vector databases, embeddings, prompt engineering, and AI orchestration patterns
- Familiarity with AI governance, lifecycle management, responsible AI, security considerations
- Experience integrating AI into data platforms, analytics, or customer-facing apps
- Knowledge of Big Data methodologies, concepts, and best practices
- Commitment to inclusion and diversity
- Travel up to 30-50%
- Hybrid role: 1-2 days in office
- collaboration
- leadership
- communication
- Databricks
- Delta Lake
- Unity Catalog
