Senior Data & AI Engineer - Managed Services
New
3
3CloudData & AI
Remote - USFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- Microsoft AzureMicrosoft Power BI
Requirements
- Bachelor’s degree in Computer Science, Mathematics, or a related field, or equivalent certification.
- Experience working in a support role and understanding standard support processes such as ITIL.
- 5+ years architecting, implementing, and supporting solutions on Microsoft Azure and Fabric data and AI tool stacks.
- Experience with Azure Data Factory (ADF), SQL DW, Azure Synapse, Azure Databricks, Microsoft Fabric, and Microsoft Power BI.
- Strong proficiency in enterprise data warehousing, semantic models, data lake architecture, and metadata-driven ETL processes.
- Experience with DevOps/DataOps, including git-based source control and automated deployment pipelines.
- Strong verbal and written communication skills.
- Client relationship skills and experience managing vendors.
- Ability to work in a fast-paced, rapidly changing environment.
- Experience implementing or supporting Agentic AI, machine learning, predictive analytics, and/or LLM use cases on Microsoft data and AI tools is preferred.
Responsibilities
- Lead support for multiple clients’ Azure Data, Databricks, and/or Fabric and Power BI environments, analyzing and resolving incidents and escalations.
- Manage and advise on assigned client services, including monitoring, governance, ETL, data warehousing, reporting, and AI/ML operations.
- Architect, implement, monitor, and support enhancements to clients’ Microsoft Azure and/or Fabric data and AI tool stacks.
- Advise customers on licensing for Microsoft data and AI solutions and explain the capabilities and limitations of licensing platforms.
- Develop data solutions that import and transform data, use medallion data lake architectures, and serve star-schema models for analytics and AI/ML applications.
- Troubleshoot client issues, follow up within contracted SLAs, and communicate ticket status and solutions to stakeholders.
- Serve as lead engineer in client meetings and communicate technical issues and solutions in business terms.
- Configure, administer, tune, and develop client data environments using governance, security, and well-architected-framework best practices.
- Maintain client environment documentation and promote best practices with clients and internally.
- Mentor and coordinate technical work for onshore and offshore engineers and collaborate with stakeholders on client solutions.
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