Solutions Engineer - Data Engineering

SHI International Corp. is a global provider of IT solutions and services, and they are seeking a Solutions Engineer for Data Engineering within their Microsoft Data and AI practice. This role involves designing, building, and delivering enterprise-scale data engineering solutions using Microsoft Azure and Microsoft Fabric, focusing on client outcomes and hands-on engineering.

Responsibilities:

• 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
• 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

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
• Microsoft Certified Azure Data Engineer Associate, required or expected within six to twelve months
• 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
• Microsoft Certified Fabric Analytics Engineer Associate or Azure Solutions Architect Expert
• 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