Principal Analytics Engineer - Analytics & AI

Duties & Responsibilities

• Design analytics solutions using software engineering best practices to ensure scalability, maintainability, and long-term supportability.
• Build reusable analytics components, semantic models, and shared data services that accelerate enterprise adoption.
• Lead adoption of AI-assisted development, automation, and engineering practices within the Analytics organization.
• Partner with software engineering and platform teams to integrate analytics into enterprise applications through APIs and event-driven architecture.
• Extract and interpret data to answer ambiguous questions while working directly with personnel across the network.
• Determine reporting, analytics, and additional analysis needed to support initiatives and measurement.
• Proactively analyze topics, identify insights, and create recommendations supported by facts to change behaviors and drive operational improvements across the team and business.
• Clearly translate and communicate complex concepts into understandable, professional presentations.
• Consult, support, and inform leadership using data-driven insights.
• Translate business needs into technical specifications and scalable analytical solutions.
• Analyze, design, develop, document, test, and deploy BI, analytics, and data solutions.
• Create engaging visualizations, dashboards, and self-service analytics products for internal and external stakeholders.
• Enhance, modernize, and support existing solutions, including migration of legacy assets where appropriate.
• Identify opportunities to automate analytics workflows and reduce manual effort through AI-enabled development, workflow orchestration, and self-service solutions.
• Contribute to the design of conversational analytics and natural-language data experiences that increase accessibility to trusted business insights.
• Evaluate and implement emerging technologies that improve analytics delivery, stakeholder experience, and team productivity.
• Establish best practices for data quality, governance, lineage, and validation to ensure trust in analytics and AI-generated outputs.
• Develop and maintain technical documentation to support long-term maintainability and knowledge sharing.
• Implement best practices for optimum use, performance, scalability, and maintainability of BI and analytics solutions.
• Provide technical leadership to the team and help build the skills of other team members.
• Mentor team members on modern BI, analytics engineering, and AI-enabled delivery practices.
• Mentor, train, and support the development of other analysts across the network.
• Present and deliver analytical value through business intelligence, storytelling, and cross-functional collaboration.
• Build relationships and consult across the network to bring solutions to life.
• Collaborate with internal analytics teams to develop solutions in tandem.
• Partner with business and technology stakeholders to develop scalable analytics products and data solutions that support strategic objectives.
• Collaborate with internal departments to understand drivers of trends and the impact of business changes.
• Collaborate with leadership to develop and maintain robust performance reporting and analytics.
• Lead project plans, process flows, and metrics; facilitate project meetings, communicate progress, and escalate blockers when needed.
• Engage with internal and external customers to identify and prioritize areas of analysis and opportunity.

Required Qualifications

• 8+ years of analytics experience developing business solutions using comprehensive, robust data assets.
• Experience with AI-enabled analytics, conversational analytics, natural-language querying, or intelligent workflow solutions.
• Experience applying software engineering principles to analytics solutions, including Git-based source control, CI/CD pipelines, automated testing, and code review practices.
• Experience developing reusable analytics frameworks, semantic models, APIs, or shared data services.
• Experience integrating AI and Large Language Models (LLMs) into analytics workflows using technologies such as Microsoft Copilot, Azure AI, OpenAI, or similar platforms.
• Experience with Python or C# for analytics automation, data processing, or AI solution development.
• Experience building cloud-native analytics solutions on Azure using services such as Azure Data Factory, Azure Functions, Logic Apps, or Fabric.
• Experience with relational and non-relational (NoSQL) databases (e.g., MongoDB, Cosmos DB, Cassandra, DynamoDB) and modern cloud data platforms.
• Experience designing data products and enterprise-scale analytics platforms rather than standalone dashboards.
• Familiarity with Infrastructure as Code, DevOps practices, and modern deployment automation.
• Experience partnering with software engineering teams to build scalable data and analytics solutions.
• Mastery proficiency with Microsoft Power BI, and strong working proficiency with the broader Microsoft Power Platform Suite of programs (Power Apps, Power Automate).
• Advanced knowledge and practical application of a programming language.
• Bachelor’s degree or a minimum of 4 years of equivalent work experience and a high school diploma/GED.

Preferred Qualifications

• Logistics and supply chain experience.
• Mastery understanding of data fundamentals, SQL Querying, and passion for data integrity, testing, and validation.
• Experience working with product teams in an iterative environment.
• Positive, collaborative working style.
• Effective communicator and data/reporting/business liaison through multiple mediums.
• Values a diverse and inclusive work environment.