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Tier-1 employer, mid-level data/AI role, metro locations, broad Azure skillset increases competition.
Azure-centric data engineering and consulting require platform-specific experience but skills remain moderately transferable across industries.
Specific Azure Data/AI skills, certifications, and explicit 4–6 years experience create strict candidate filters.
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Own timely execution of deliverables as a key individual contributor on Data and AI projects, managing estimates, priorities, and scope adjustments.
Design, develop, and deploy complex data and AI solutions leveraging Microsoft Azure Data Services and related technologies to meet customer business objectives.
Identify and manage risks and dependencies beyond immediate scope, while driving adoption of Microsoft cloud and AI solutions and collaborating with sales and account teams to grow strategic relationships.
4-6 years of professional experience in data engineering or related roles.
Bachelor's degree in Computer Science Engineering or equivalent; higher education preferred.
Hands-on experience with Azure Data Services, Data Engineering across cloud/on-prem/hybrid, Azure Synapse Analytics, and ETL/ELT tools like Azure Data Factory.
Knowledge or certification in Microsoft Azure Data Engineer/Azure AI Engineer or equivalent industry certifications is a plus.
Experienced in technical solution design and delivery for complex enterprise data and AI projects using Microsoft technologies, comfortable working individually and with senior consultants.
Demonstrates strong engineering practices including Agile, DevOps (Azure DevOps), DataOps/MLOps with practical knowledge of CI/CD pipelines, automated testing, and secure coding.
Capable of engaging with business stakeholders to translate technical concepts and co-create innovative, value-driven solutions in ambiguous and changing environments.