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 MLOps platforms
  
  


• 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
  
  

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 through enterprise 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