What are the responsibilities and job description for the Cloud BI Engineer (3 Days in OFFICE :: W2 Only) position at VAAM Technologies?
Key Responsibilities
- Design and build end-to-end data pipelines and ingestion workflows using Azure Data Factory and Microsoft Fabric, ensuring scalability, observability, and data quality at every stage.
- Develop and maintain serverless automation and event-driven integrations using Azure Function Apps and Logic Apps, including orchestration flows that connect AI services to data pipelines.
- Own infrastructure-as-code practices using Terraform to provision and manage cloud resources consistently across environments.
- Drive CI/CD pipeline development and deployment automation through GitHub Actions and Harness, ensuring fast, safe, and repeatable deployments across both data and AI workloads.
- Integrate Azure AI Services and Azure OpenAI into data workflows - including document intelligence, embeddings, semantic search, and AI-assisted data enrichment - enabling the platform to support intelligent applications and copilot-style experiences.
- Architect/Manage analytical workloads within Azure Synapse Analytics, including Lakehouse patterns, dedicated SQL pools, and Spark-based transformations.
- Support cross-cloud strategies by applying AWS knowledge to maintain contingency pipelines and hybrid architecture patterns.
- Maintain continuity of existing pipelines and maintenance work.
Qualifications & Requirements
- Around 10 years of experience in data engineering with a strong focus on cloud-native solutions.
- Deep hands-on expertise with the Microsoft Azure data stack, including Azure Data Factory, Microsoft Fabric, Synapse Analytics, Logic Apps, and Function Apps.
- Proven experience with infrastructure-as-code using Terraform, and CI/CD platforms such as GitHub Actions and Harness.
- Strong proficiency in SQL and at least one data-oriented programming language, with Python preferred given its centrality to AI and ML integration work.
- Demonstrated experience integrating Azure AI Services or Azure OpenAI into data pipelines or platform workflows, including working with REST-based AI APIs, prompt engineering, embeddings, or AI-assisted data processing.
- Practical experience publishing data to SharePoint Lists from ADF pipelines, including familiarity with SharePoint Online REST APIs and OAuth authentication flows.