Role Description We are seeking a highly skilled and business-focused Data Warehouse Manager to lead the strategy, architecture, development, governance, and operational support of our enterprise data warehouse and analytics platforms. This role will oversee the design and management of modern cloud-based data platforms, data integration pipelines, semantic models, reporting environments, and AI-ready data foundations supporting ERP, CRM, ecommerce, supply chain, finance, and operational analytics. The ideal candidate combines strong technical leadership with business process knowledge and experience managing enterprise-scale data environments in manufacturing, distribution, or ecommerce organizations. This individual must be a hands-on “player-coach” with advanced technical skills who can both lead a team and actively contribute to architecture, engineering, troubleshooting, and delivery execution. Key Responsibilities - Data Warehouse & Platform Leadership - Lead the administration, architecture, and optimization of the enterprise data warehouse environment. - Manage modern cloud data platforms including Microsoft Fabric, SQL Server, Lakehouse/Warehouse platforms, and related analytics technologies. - Define and maintain enterprise data architecture standards, modeling strategies, naming conventions, and governance practices. - Oversee dimensional modeling, semantic models, curated datasets, and enterprise KPI frameworks. - Data Integration & Engineering - Manage end-to-end data pipelines integrating ERP, CRM, ecommerce, WMS, finance, and third-party systems. - Oversee ELT/ETL development, orchestration, monitoring, and optimization. - Ensure secure and scalable API/OData-based integrations across enterprise applications. - Partner with application teams to support data onboarding and system harmonization initiatives. - Analytics & Reporting - Support enterprise reporting and self-service analytics using Power BI and Excel. - Manage shared semantic models, reusable business measures, and governed reporting datasets. - Collaborate with business stakeholders to deliver operational dashboards and executive reporting. - Ensure data freshness, performance optimization, and reporting reliability. - Data Governance & Quality - Implement enterprise data governance processes, stewardship, and master data management practices. - Develop data quality monitoring, reconciliation, lineage, and audit controls to drive compliance with the agreed-upon data governance plan. - Partner with business leaders to support data ownership, stewardship, and governance accountability across the organization. - Maintain security models and role-based access controls for sensitive data domains. - Leadership & Team Management - Lead, mentor, and develop a high-performing team of data engineers while incorporating offshore and contract resources into the overall delivery model. - Serve as a hands-on 'player-coach' leader capable of both managing the team and actively contributing to architecture, troubleshooting, optimization, and solution delivery. - Provide advanced technical leadership across data engineering, semantic modeling, integration architecture, and analytics platforms. - Establish development standards, deployment processes, operational support procedures, and technical best practices. - Manage project prioritization, vendor coordination, resource planning, and cross-functional collaboration. - Drive accountability, continuous improvement, and delivery execution across the data and analytics organization. - AI & Advanced Analytics Enablement - Support AI/ML and Copilot initiatives by building AI-ready enterprise data foundations. - Enable near real-time analytics, automation, and operational intelligence capabilities. - Partner with digital transformation and enterprise systems teams on strategic initiatives. Qualifications - Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field, or 5+ years of equivalent hands-on experience in data warehousing, analytics, or data engineering environments. - 7+ years of experience in data warehousing, BI, or enterprise analytics environments. - 3+ years of experience managing and developing technical teams. - Proven experience operating as a hands-on technical leader with strong architecture and troubleshooting capabilities. - Strong background supporting data and analytics environments within manufacturing and distribution organizations. - Good understanding of how sales performance, customer segmentation, pricing, channel performance, and operational KPIs are measured within manufacturing and distribution environments. - Good understanding of ecommerce performance metrics, digital customer behavior, conversion analytics, and Google Analytics reporting within B2B and B2C ecommerce environments. - Strong experience with Microsoft Fabric, SQL Server / T-SQL, Power BI, Power Platform, Dataverse architectures, Data Lake/Lakehouse architectures, and API/OData integrations. - Experience designing and managing enterprise-scale ETL/ELT pipelines. - Strong understanding of dimensional modeling, semantic models, data ontology, enterprise data relationships, and governed business data structures. - Experience supporting ERP, CRM, and operational systems integrations. - Must have experience working in Git and/or Azure DevOps-based development environments, including source control, branching strategies, CI/CD pipelines, release management, and agile development practices. - Strong verbal, written, and presentation communication skills with the ability to communicate effectively across both technical and non-technical audiences. - Strong leadership and stakeholder management skills. Preferred Qualifications - Experience integrating systems such as Microsoft Dynamics NAV / Business Central, Dynamics 365 CRM, ecommerce platforms, and WMS systems. - Experience with Azure AI / OpenAI services, Databricks or PySpark, AI agents and automation platforms, Master Data Management (MDM), and Enterprise API architecture. - Familiarity with DevOps and CI/CD deployment practices. Technical Skills - Microsoft Fabric - Power BI - SQL Server / PostgreSQL - Power Platform - Dataverse - DAX - Data Modeling - Data Ontology & Semantic Modeling - REST APIs / OData - Python or Spark (preferred) - Git / Azure DevOps - Data Governance & Security Success Metrics - Improved enterprise reporting performance and data reliability. - Increased adoption of governed self-service analytics. - Reduced data latency and faster delivery of operational insights. - Improved data quality and consistency across systems. - Scalable foundation for AI and advanced analytics initiatives. Leadership Competencies - Strategic thinker with strong operational execution. - Strong collaboration across business and technical teams. - Ability to simplify complex technical concepts for business stakeholders. - Process-oriented with strong governance discipline. - Continuous improvement mindset with focus on scalability and automation. Physical/Environmental Requirements - Frequently remains in a stationary position and occasionally moves about the office or worksite to access files, supplies, or attend meetings. - Frequently uses hands and fingers to operate office equipment such as a keyboard, mouse, telephone, and other standard office tools. - Must be able to visually assess information on screens, documents, and reports. - Frequently reads, interprets, and analyzes written and visual information. - Occasionally lifts or moves items up to 10–15 pounds (e.g., files, laptop, meeting materials). - Must be able to effectively communicate information and ideas in person, via video conference, and through written communication. - Works primarily in an office or remote office environment with standard business equipment. - May require extended periods of screen time. - May occasionally be required to attend meetings or events outside of normal workspace or business hours. Accommodation Candidates for the position should be able to perform essential job duties in described work environment with or without accommodation. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Equal Employment Opportunity Infinite Electronics is proud to be an Equal Employment Opportunity and Affirmative Action employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, marital status, age, national origin, disability status, protected veteran status, or any other characteristic protected by law. We are committed to building a diverse workforce.

• Perform Data Architecture support for projects and enhancements, including crafting and executing data management, architecture, integration, and governance strategies. • Provide technical leadership for architecture, design, documentation, and maintenance of databases and related systems, including creating database storage structures, resolving database issues, and maintaining system security. • Support development and implementation of business applications that optimize statistical efficiency and data quality. • Identify, analyze, and interpret trends or patterns in complex data sets. • Monitor daily operations of data loads, identify data discrepancies and data quality issues, and ensure data consistency and integrity. • Participate in project and enhancement estimation exercises and project team meetings, providing input, task status, risk identification, mitigation strategies, and issue management. • Collaborate with business partners to transform business requirements into environment-specific ETL, reporting, and data validation designs, and prioritize business and information needs. • Design relational databases and physical data models to support enterprise applications, data acquisition, and security requirements. • Review database changes to ensure no performance or functionality impacts and ensure production stability.

• Designing, building, and maintaining data pipelines using Python and SQL • Developing and managing data models within Microsoft Fabric Data Warehouse • Creating, publishing, and optimizing Power BI dashboards and reports for business stakeholders • Collaborating with analysts and business teams to understand reporting requirements and translate them into scalable data solutions • Ensuring data quality, consistency, and performance across ingestion and transformation layers

• Build and maintain robust data pipelines processing large volumes of data • Update and optimise our data platform for speed, scalability and cost • Coordinate with different functional teams to understand and meet their data needs • Develop processes and tools to monitor and analyse model performance and data accuracy • Solve general data-related problems