Data & Analytics Leader
1 month ago
As a Data & Analytics Leader at AuxoAI, you will be responsible for leading key data initiatives, including cloud transformation, data governance, and AI projects. Your role will involve defining cloud architectures, guiding data science teams in model development, and ensuring alignment with data architecture principles across complex solutions.
Key Responsibilities:
- Drive several 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 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.
- Guide application development teams in the data design of complex solutions, ensuring alignment with 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.
Requirements:
- Strong cloud data architecture knowledge (preference for Microsoft Azure).
- 8-10+ years of experience in data architecture, with proven experience in cloud data transformation, MDM, data governance, and data science capabilities.
- Ability to lead software evaluations, including RFP development, capabilities assessment, formal scoring models, and delivery of executive presentations.
- Well-versed in data domains, including data warehousing, data governance, MDM, data quality, data standards, data catalog, analytics, BI, operational data store, metadata, unstructured data, non-traditional data, and multimedia.
- Experience with cloud data technologies, such as Azure Data Factory, Azure Data Fabric, Azure Storage, Azure Data Lake Storage, Azure Data Bricks, Azure AD, and Azure ML.
- Experience with big data technologies, such as Cloudera, Spark, Sqoop, Hive, HDFS, Flume, Storm, and Kafka.
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