Since 1989, SHI International Corp. has helped organizations change the world through technology. We’ve grown every year since, and today we’re proud to be a $16 billion global provider of IT solutions and services.
Over 17,000 organizations worldwide rely on SHI’s concierge approach to help them solve what’s next. But the heartbeat of SHI is our employees – all 7,000 of them. If you join our team, you’ll enjoy:
Our commitment to diversity, as the largest minority- and woman-owned enterprise in the U.S.
Continuous professional growth and leadership opportunities.
Health, wellness, and financial benefits to offer peace of mind to you and your family.
World-class facilities and the technology you need to thrive – in our offices or yours.
Role Description
Design, develop, and implement data ingestion, transformation, and integration pipelines using Azure Data Factory, Azure Synapse Analytics, Microsoft Fabric, and related Azure data services
Build and optimize data lakehouse and warehouse solutions in Azure and Microsoft Fabric, ensuring scalability, reliability, security, and cost effectiveness
Develop and maintain data models, ETL and ELT processes, and historical data versioning logic to support complex multi source datasets
Configure and manage Azure Data Lake Storage Gen2 environments, including data organization, lifecycle management, and archival strategies
Implement data validation, cleansing, reconciliation, and quality controls to ensure trusted and auditable data platforms
Collaborate with BI and analytics teams to prepare data for downstream reporting, analytics, and AI consumption
Apply security best practices including encryption, identity based access control, and compliance with standards such as HIPAA, PII handling, and NIST 800 53
Support data governance practices including lineage, access patterns, and operational readiness
Implement monitoring and operational reporting for pipelines and data platforms to support production support models
Work with structured, semi structured, and unstructured data sources across cloud and on premises environments
Participate in technical workshops, discovery sessions, and requirements gathering with clients and internal teams
Translate business requirements into actionable technical solutions focused on client outcomes
Produce high quality technical documentation including design artifacts, migration plans, and operational runbooks
Contribute to reusable frameworks, templates, and engineering best practices within the Data and AI practice
Participate in code reviews, testing, and quality assurance processes
Follow modern engineering practices including source control, CI CD, and environment promotion strategies
Support post implementation activities including troubleshooting, optimization, and client enablement
Demonstrate ownership and accountability for assigned deliverables and proactively address delivery risks
Behaviors and Competencies
Presenting: Can design and deliver engaging presentations, adapting the content and style to suit the audience, context, and medium.
Negotiation: Can proactively seek out negotiation opportunities, initiate discussions, and contribute to conflict resolution.
Communication: Can effectively communicate complex ideas and information to diverse audiences and can facilitate effective communication between others.
Detail-Oriented: Can manage complex tasks or projects, identifying errors or inconsistencies, and ensuring all details are addressed, necessary corrections are made, and quality is maintained.
Organization: Can effectively coordinate multiple projects, delegate tasks where appropriate, and employ advanced organizational tools and methods.
Follow-Up: Can proactively identify tasks that require follow-up, initiate necessary actions, and contribute to efficient workflow management.
Problem-Solving: Can proactively identify potential problems, initiate preventive measures, and propose and contribute to innovative solutions.
Relationship Building: Can proactively seek out opportunities to expand networks, initiate collaborations, and contribute to team cohesion.
Documentation: Can develop comprehensive documentation standards, implement best practices, and ensure documentation supports operational efficiency.
Results Orientation: Can set challenging goals for their team and lead them to achieve these goals, demonstrating a consistent track record of results.
Skill Level Requirements
Proven hands-on experience delivering modern data engineering solutions on Microsoft Azure and or Microsoft Fabric, including data ingestion, transformation, storage, and analytics enablement
Strong engineering foundation across data pipelines, Lakehouse or warehouse architectures, and relational data platforms, with practical experience using services such as Azure Data Factory, Azure Synapse, Databricks, SQL Server, Azure SQL, ADLS Gen2, and Microsoft Fabric
Experience designing and operating production data platforms, including data modeling, incremental processing, historical retention, monitoring, and operational support
Solid understanding of data security, governance, and compliance concepts, including identity-based access, encryption, and working with sensitive or regulated data
Experience working in consulting or project-based delivery environments, collaborating with engineers, project managers, and client stakeholders
Familiarity with modern engineering practices such as source control, CI CD, testing, and environment promotion
Strong analytical, problem-solving, and communication skills, with the ability to translate business needs into practical technical solutions
Certifications
Microsoft Certified Azure Data Engineer Associate, required or expected within six to twelve months
Preferred, Microsoft Certified Fabric Analytics Engineer Associate or Azure Solutions Architect Expert
Other Requirements
Ability to travel to SHI, Partner, and Customer Events
Ability to work independently and as part of a collaborative, cross-functional team.
Commitment to continuous learning and professional development in Microsoft technologies and data visualization trends.
Strong ethical standards and adherence to data privacy, governance, and security policies.
Preferred Requirements
Experience with dimensional and Lakehouse data modeling patterns
Advanced proficiency in Azure Data Factory, Azure Synapse, Microsoft SQL Server, Azure SQL Database, Azure Data Lake Storage, and Microsoft Fabric.
Experience operating and supporting production data platforms
Experience implementing CI CD and infrastructure as code concepts
Familiarity with Power BI operational reporting and monitoring templates
Strong facilitation skills in client-facing and internal settings
Experience delivering data platforms for public sector or regulated industry clients
Experience supporting analytics, reporting, and AI-ready data workloads
Experience contributing to reusable engineering frameworks, templates, or delivery standards
Experience with Azure Databricks for advanced data engineering, transformation, and analytics.
Experience with Microsoft Fabric, especially in integrated data engineering and analytics workflows.
Experience with data pipeline monitoring and automated operational reporting.
Facilitation and collaboration skills in team and client-facing settings.
The estimated annual pay range for this position is $156,000 - $181,000 which includes a base salary and bonus. The compensation for this position is dependent on job-related knowledge, skills, experience, and market location and, therefore, will vary from individual to individual. Benefits may include, but are not limited to, medical, vision, dental, 401K, and flexible spending.
Equal Employment Opportunity – M/F/Disability/Protected Veteran Status

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