Azure AI Data Analyst

Role Summary

Detailed Responsibilities

• Collaborate with IT and data science teams to gather technical requirements and ensure data availability and system readiness.
• Design, build, and optimize ETL/ELT pipelines to prepare datasets for machine learning models and large language models.
• Work in Google Cloud environments to manage datasets, orchestrate data flows, and support model deployment.
• Troubleshoot system, API, and data pipeline issues by analyzing anomalies, logs, and technical options.
• Develop technical documentation for data architectures, API integrations, and AI workflows.
• Configure, test, and deploy agentic AI development and workflow orchestration platforms.

Knowledge, Skills, and Competencies

• Strong collaboration, analytical, technical, troubleshooting, and problem-solving skills.
• Strong technical documentation skills covering architectures, data pipelines, and system integrations.
• Understanding of data engineering, database management, and the software development life cycle.
• Proficiency in Python with Pandas and NumPy, plus robust SQL for complex querying and data manipulation.
• Understanding of machine learning, generative AI, agentic development, and AI orchestration platforms such as Flowise AI, Zapier, and n8n.
• Familiarity with Google Cloud technologies including Gemini, BigQuery, and Vertex AI.
• Strong experience with Azure Synapse and Google BigQuery.
• Understanding of relationships among cloud environments, APIs, databases, data pipelines, and servers.

Experience and Education

• The posting states a minimum of 3 years of professional experience and also states 1 to 3 years of relevant experience in similar roles.
• A bachelor's degree or equivalent combination of education and experience is listed, with educational requirements varying by geography.

Work Environment

• Duties are performed in a normal office environment and may require extended sitting, sustained visual concentration, and repetitive computer-based movements.