Analytics Engineer

Role overview Join a corporate Data & Analytics team to design and deliver scalable, governed data products that power enterprise reporting, self-service analytics, and emerging AI-enabled experiences. The role bridges business partnership and hands-on technical build, translating operational needs into reliable data solutions on a modern analytics platform.

Responsibilities - Partner with business leaders, subject-matter experts, and end users to understand processes, challenges, goals, and reporting needs. - Lead discovery and requirements-gathering sessions; document business rules, data definitions, use cases, and success measures. - Translate business needs into scalable data solutions, including curated data products, semantic models, dashboards, and AI-ready assets. - Design, build, and maintain end-to-end components within Microsoft Fabric, including pipelines, notebooks, lakehouses, warehouses, and semantic models. - Develop and optimize DAX measures, reusable semantic models, and Power BI reports focused on accuracy, performance, and consistency. - Own solutions through discovery, design, development, testing, deployment, adoption, and ongoing support, while promoting reuse and lifecycle standards.

Requirements - Bachelor's degree in Information Systems, Computer Science, Data Analytics, Engineering, Business Analytics, or a related field, or equivalent practical experience. - Professional experience in analytics engineering, business intelligence, data engineering, or a similar discipline. - Strong experience building enterprise data and analytics solutions, including semantic models, DAX, and Power BI delivery. - Solid SQL skills and experience with relational and analytical data stores. - Knowledge of dimensional modeling, star schemas, data warehousing, and data quality practices. - Ability to communicate effectively with business stakeholders, technical teams, and cross-functional partners.

Nice to have - Hands-on experience with Microsoft Fabric, including Data Factory pipelines, Lakehouse, Warehouse, notebooks, and semantic models. - Experience developing data transformations or automation using Python or similar languages. - Familiarity with Git, Azure DevOps, deployment pipelines, testing, and CI/CD practices. - Experience integrating data from REST APIs, SaaS platforms, SQL Server, and cloud-based sources.

Benefits and work setup - Posted annual expected pay range of $120,000–$150,000 USD, with eligibility for performance-based bonus opportunities. - Company-subsidized medical coverage, plus company-paid life and short- and long-term disability insurance. - 401(k) match, tuition assistance, and access to cross-training on a variety of projects. - Opportunity to work with a national firm spanning multiple U.S. locations, collaborating with cross-functional business and IT stakeholders.