Senior Analytics Engineer

Hybrid Details: Must be located near one of the following cities for conversion: Raleigh, NC; Charlotte, NC; Lisle, IL; Tampa, FL; Jacksonville, FL; Pensacola, FL; Columbus, IN; San Antonio, TX; Houston, TX; Tempe, AZ; Bloomington, MN; Akron, OH; Nashville, TN; Greenwood Village, CO; Corona, CADuration: 6 months to start (with potential for conversion)Job DescriptionWe are seeking a highly skilled and experienced Senior Analytics Engineer with expertise in Microsoft technologies to join our dynamic teamThe ideal candidate will be responsible for designing, developing, and maintaining business intelligence solutions, with a strong emphasis on semantic layer design and scalable data modeling. This role will involve collaborating with cross-functional teams to gather requirements, design data models, and implement robust BI solutions to support business objectives. Key Responsibilities:Design And Development Of BI SolutionsArchitect, design, and develop end-to-end business intelligence solutions using the Microsoft BI stack. Design, develop, and maintain scalable semantic layers to support enterprise reporting and analytics. Define data models, metrics, and KPIs for reporting and analytics. Lead efforts to design and optimize scalable multidimensional and tabular data models using SSAS/AAS and modern semantic modeling approaches. Demonstrate strong proficiency in DAX, Power Query, and SQL, along with designing intuitive and interactive Power BI dashboards. Work with modern data platforms including Snowflake to support analytics and reporting workloads. Project Management And CollaborationManage project timelines, priorities, and deliverables effectively. Collaborate with cross-functional teams to deliver high-quality BI solutions. Communicate effectively with stakeholders to gather and refine requirements. Serve as a best practices resource for BI and analytics initiatives. Conduct training sessions and enablement for business users on modern BI tools. Mentor and guide junior team members on BI and data modeling best practices. Administration And DocumentationMonitor and administer Power BI service capacities and environments. Troubleshoot, debug, and optimize BI solutions (reports, cubes, and semantic models). Define and maintain BI frameworks, semantic layers, and metadata repositories to support data governance. Document data warehouse structures, BI solutions, and metadata. Act as an escalation point for Power BI-related issues. Create and maintain technical documentation for BI tools and solutions. Qualifications: Bachelor s degree in Computer Science, Engineering, or related field. 5 7 years of experience designing and developing BI solutions using Microsoft technologies. Strong proficiency in SQL, SSAS/AAS tabular modeling, DAX, Power BI, Paginated Reports, Gateway, Service, and Security. Experience working with Azure-based BI solutions (Azure SQL, Synapse, Data Factory, Data Lakes). Experience working with Snowflake, including data modeling and delivering analytics via Power BI. Strong experience designing semantic layers (core requirement). Experience with Power BI Service administration and capacity governance. Strong problem-solving, analytical, and communication skills. Hands-on experience with ETL development and data integration. Must-Have Skills:Extensive knowledge of Microsoft AAS/SSAS in developing cubes. Extensive knowledge of Microsoft Fabric and related tools. Strong expertise in semantic layer design and data modeling. Advanced knowledge of Power Query and DAX. Experience using Git for version control and deployment. Must have hands-on experience working with Snowflake. Experience working with Databricks. Preferred (Nice-to-Have) Skills:Experience with AI-driven analytics and reporting, including tools such as Microsoft Copilot and Snowflake Cortex. Relevant certifications (e.g., Microsoft Certified: Data Analyst Associate, Azure Data Engineer Associate, Power BI). Experience with PowerShell. Experience coding in Python. Experience on MCP server integration and LLM models. Experience working and configuring AI Data Agents. Behavioral Competencies:Self-motivated with strong problem-solving abilities. Ability to work effectively across all levels of the organization. High attention to detail and commitment to quality. Ability to operate with urgency in ambiguous or high-risk situations. Strong collaboration skills and team-oriented mindset.