1185.25 Data Architect

Data Architect

Key Responsibilities

• Design enterprise-scale Data, Big Data, Analytics, and AI platforms
  
• Architect Data Lakes, Lakehouses, Data Warehouses, Data Marts, and Big Data environments
  
• Design architectures supporting structured, semi-structured, and unstructured data
  
• Establish data platform standards, reference architectures, and best practices
  
• Design highly scalable batch, streaming, and real-time data processing ecosystems
  
• Define enterprise patterns for data ingestion, integration, transformation, orchestration, and delivery
  
• Design and govern data architectures supporting AI, Machine Learning, Advanced Analytics, and Generative AI workloads
  
• Ensure enterprise data is discoverable, trusted, governed, and consumable for AI initiatives
  
• Design metadata, lineage, cataloging, and semantic layer capabilities required for AI adoption
  
• Establish architecture standards supporting RAG, Knowledge Graphs, Vector Stores, AI Agents, and MLOpsplatforms
  
• Define processes and controls to improve data quality and data reliability for AI model training and inference
  
• Collaborate with Data Science and AI teams to ensure data platforms meet AI readiness requirements
  

Required Skills

• 10+ years of experience in Data Architecture, Big Data Architecture, or Enterprise Information Management
  
• Strong hands-on experience designing and implementing enterprise on-premises data platforms
  
• Proven experience designing large-scale Data Warehouses, Data Lakes, and Lakehouse platforms
  
• Experience designing Big Data environments handling high-volume and high-velocity workloads
  
• Experience establishing enterprise data governance and data quality frameworks
  
• Experience supporting AI, Machine Learning, and Advanced Analytics initiatives throughenterprise data architecture
  
• Experience working with distributed processing and storage platforms
  
• Spark, Kafka, Iceberg, Airflow, NiFi, Trino, Flink, HDFS, Ozone, MinIO, Cloudera, and Stackable
  
• PostgreSQL, Oracle, SQL Server, and MongoDB
  
• Vector Databases and Knowledge Graph Platforms
  
• Ataccama, Alation, Collibra, OpenLineage, and Informatica
  
• Power BI, Tableau, and Superset