This role is responsible for designing and supporting the data architecture that enables AI and machine learning initiatives across the organization. The ideal candidate will bring a strong blend of data architecture, cloud and data engineering, and AI enablement experience, ensuring that data is structured, accessible, and optimized for AI-driven use cases. This individual will work closely with engineering, analytics, and business teams to translate requirements into scalable data solutions.
Key Responsibilities
- Design and implement data architectures to support AI and machine learning use cases, including data lake, warehouse, and feature stores
- Develop data models, pipelines, and integration patterns across structured and unstructured data sources (e.g. Snowflake, Postgres, Azure, BigQuery, etc.) for consumption by AI/ML.
- Design and implemented integration patterns that connect structured and unstructured data sources (Snowflake, Salesforce, SharePoint, PDFs, APIs) into unified, AI-ready datasets.
- Define standards for real-time and batch data ingestion, transformation, storage, and access
- Collaborate with engineering and AI teams to ensure data readiness for model development and deployment
- Support data governance practices, including data quality, lineage, and access controls
- Evaluate and recommend tools and technologies to support AI data workflows (e.g., data platforms, vector stores)
- Document architecture patterns and provide guidance to technical and business stakeholders
Required Skills & Experience
- 7+ years of experience in data architecture, data engineering, or related roles
- Strong experience with cloud-based data platforms (e.g., Snowflake, BigQuery, or similar)
- Proficiency in SQL and familiarity with Python or similar scripting languages
- Experience designing data models and building ETL/ELT pipelines
- Understanding of data requirements for AI/ML use cases (e.g., feature engineering, unstructured data)
- Strong communication skills and ability to work across technical and business teams
Preferred Skills & Experience
- Experience supporting AI/ML or GenAI initiatives
- Familiarity with cloud platforms (AWS, Azure, or GCP)
- Exposure to vector databases, RAG pipelines, or AI data frameworks
- Experience with data governance, cataloging, or lineage tools