Senior Data Architect (AI & AI-Assisted Development)

Tasks

• Architect analytics solutions with SQL engines
• Build LLM based analytics solutions
• Build batch data pipelines
• Build near real time data pipelines
• Define enterprise data models
• Design scalable Data Warehouse architecture
• Design scalable lakehouse architecture
• Document AI assisted architecture patterns
• Enable NLQ capabilities
• Establish metadata and data cataloging
• Establish security standards and compliance
• Implement AI governance controls
• Implement RAG applications
• Implement data governance frameworks
• Implement data quality practices
• Implement vector database solutions
• Integrate AI and ML into data platforms
• Manage data lineage and data tagging
• Mentor teams on data architecture methodologies
• Optimize query performance
• Translate business requirements into data products

Perks/Benefits

• Continued Career Development
• Employee resource groups
• Flexible WFH policy
• Generous PTO policy
• Paid volunteer time
• Phone and internet reimbursement
• Wellness programs
• Work-life balance

Skills/Tech-stack

AI Governance | Cloudera Data Platform | Compliance | Data Catalog | Data Governance | Data Lineage | Data Modeling | Data Pipelines | Data Stewardship | Data Warehousing | Data fabric | Data mesh | Data platform | Dimensional Modeling | Enterprise Security | Explainability | HDFS | Hadoop | Hadoop Based Architectures | Hive | Iceberg | Impala | Kafka | Kudu | LLM | Lakehouse | Metadata Management | Milvus | Model Governance | Monitoring | Natural Language | Natural language interfaces | Normalized Data | Normalized data modeling | PostgreSQL | Python | Qdrant | Query Optimization | RAG | Responsible AI | Retrieval-Augmented Generation | SQL | Spark | Streaming Architectures | Vector Databases