Azure AI Data Analyst
New
J
JobgetherEnterprise AI
Fully remote working arrangement within India.Full-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- At least 3 years of professional experience, with 1–3 years of directly relevant experience in similar data or IT roles.
- Required Skills
- PythonSQLGCPNumpyPandasGenerative AI
Requirements
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related technical discipline, or equivalent education and professional experience.
- At least 3 years of professional experience, including 1–3 years directly relevant to similar data or IT roles.
- Strong hands-on experience with Azure Synapse and Google BigQuery.
- Proficiency in Python, including Pandas and NumPy.
- Strong SQL skills, including complex queries, database manipulation, and optimization.
- Good understanding of data engineering principles, database management, ETL/ELT processes, and the software development lifecycle.
- Familiarity with Google Cloud data and AI technologies, particularly Gemini, BigQuery, and Vertex AI.
- Understanding of fundamental machine learning concepts and practical familiarity with generative AI applications, LLMs, and agentic AI development.
- Exposure to AI workflow orchestration and automation platforms such as Flowise AI, Zapier, or n8n.
- Good understanding of cloud infrastructure components and their interactions, including APIs, databases, pipelines, servers, and cloud environments.
- Strong analytical, troubleshooting, and problem-solving abilities.
- Ability to create technical documentation, including architecture diagrams, pipeline descriptions, and system integration documentation.
- Ability to collaborate with technical teams and cross-functional stakeholders.
- Ability to manage multiple technical priorities while maintaining accuracy, quality, and attention to detail.
Responsibilities
- Collaborate with IT, Data Engineering, and Data Science teams to gather technical requirements and ensure data availability and system readiness for AI integration.
- Design, develop, implement, and optimize ETL/ELT pipelines to prepare, clean, transform, and structure datasets for machine learning models and LLMs.
- Build and maintain scalable data architectures for enterprise AI applications and advanced analytics.
- Manage datasets and orchestrate data workflows in Google Cloud to support AI model deployment.
- Use Azure Synapse and Google BigQuery to manage, process, and analyze enterprise data.
- Provide technical support for generative AI applications, agentic workflows, and internal data integration tools.
- Troubleshoot system, API, and pipeline issues by investigating anomalies and logs, identifying root causes, and implementing solutions.
- Participate in configuring, testing, and deploying agentic AI development platforms and workflow orchestration tools.
- Support integrations across cloud environments, databases, APIs, servers, and enterprise IT infrastructure.
- Develop and maintain technical documentation for data architectures, pipelines, API integrations, and AI workflows.
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