Data Engineer - Azure Lakehouse & AI Pipelines

SHI; Austin (TX); On-site; USD 156,000 - 181,000; Full time

Job summary

SHI Services Solutions Engineer, Data Engineering, is a key contributor within SHI's Microsoft Data and AI practice. This role designs, builds, and delivers enterprise-scale data engineering solutions using the Microsoft Azure and Microsoft Fabric ecosystems.

The Solutions Engineer works closely with Solution Engineers, Principal Engineers, Project Managers, and client stakeholders to implement secure, scalable, and compliant data platforms and pipelines that support analytics, reporting, and AI

Qualifications

• Proven hands-on experience delivering modern data engineering solutions on Microsoft Azure and/or Microsoft Fabric.
• Experience designing and operating production data platforms for analytics, reporting and AI workloads.
• Knowledge of data security, governance, and compliance concepts.

Responsibilities

• Design, develop, and implement data ingestion, transformation, and integration pipelines using Azure data services.
• Build and optimize data lakehouse and warehouse solutions for scalability, security, and cost effectiveness.
• Develop data models, ETL/ELT processes, and data versioning for multi-source datasets.
• Configure and manage Azure Data Lake Storage Gen2 environments and data lifecycle management.
• Collaborate with BI/analytics to prepare data for reporting and AI consumption.
• Apply encryption and identity-based access controls to ensure data security and compliance.

Skills

Data engineering

Security & governance

Client collaboration

Tools

Azure Data Factory

Azure Synapse Analytics

Microsoft Fabric

Databricks

SQL Server

Azure SQL

ADLS Gen2

Job description

SHI Services Solutions Engineer, Data Engineering, is a key contributor within SHI's Microsoft Data and AI practice. This role designs, builds, and delivers enterprise-scale data engineering solutions using the Microsoft Azure and Microsoft Fabric ecosystems.

The Solutions Engineer works closely with Solution Engineers, Principal Engineers, Project Managers, and client stakeholders to implement secure, scalable, and compliant data platforms and pipelines that support analytics, reporting, and AI