Auxo AI - Data Architect

Overview

As a Data & Analytics Architect, you will lead key data initiatives, including cloud transformation, data governance, and AI projects. You'll define cloud architectures, guide data science teams in model development, and ensure alignment with data architecture principles across complex solutions. Additionally, you will create and govern architectural blueprints, ensuring standards are met and promoting best practices for data integration and consumption.

• Play a key role in driving a number of data and analytics initiatives including cloud data transformation, data governance, data quality, data standards, CRM, MDM, Generative AI and data science.
• Define cloud reference architectures to promote reusable patterns and promote best practices for data integration and consumption.
• Guide the data science team in implementing data models and analytics models.
• Serve as a data science architect delivering technology and architecture services to the data science community.
• In addition, you will also guide application development teams in the data design of complex solutions, in a large data eco-system, and ensure that teams are in alignment with the data architecture principles, standards, strategies, and target states.
• Create, maintain, and govern architectural views and blueprints depicting the Business and IT landscape in its current, transitional, and future state.
• Define and maintain standards for artifacts containing architectural content within the operating model.
  
  

Location : Strong cloud data architecture knowledge (preference for Databricks)

• Experience developing architecture strategies and plans to enable cloud data transformation, MDM, data governance, and data science capabilities.
• Design reusable data architecture and best practices to support batch/streaming ingestion, efficient batch,real-time, and near real-time integration/ETL, integrating quality rules, and structuring data for analytic consumption by end uses.
• Ability to lead software evaluations including RFP development, capabilities assessment, formal scoring models, and delivery of executive presentations supporting a final recommendation.
• Well versed in the Data domains (Data Warehousing, Data Governance, MDM, Data Quality, Data Standards, Data Catalog, Analytics, BI, Operational Data Store, Metadata, Unstructured Data, non-traditional data and multi-media, ETL, ESB).
• Experience with cloud data technologies such as Azure data factory, Azure Data Fabric, Azure storage, Azure data lake storage, Azure data bricks, Azure AD, Azure ML etc.
• Experience with big data technologies such as Cloudera, Spark, Sqoop, Hive, HDFS, Flume, Storm, and Kafka
  
  

(ref:hirist.tech)