Senior Analytics Engineer

Position Summary

This is a 100% onsite role. Remote and/or hybrid arrangements will not be considered.

What We’re Looking For

• Solve business problems before recommending technology.
• Embrace AI as a force multiplier rather than a future initiative.
• Deliver working solutions quickly and iterate based on feedback.
• Adapt as enterprise technologies evolve.
• Continuously learn and challenge conventional approaches.
• Balance architectural discipline with pragmatic execution.

Education & Experience

• Minimum of five (5) years of work experience designing, developing, and delivering enterprise analytics, reporting, or business intelligence solutions.
• Advanced proficiency in SQL, including complex query development, performance optimization, and data transformation.
• Experience designing and implementing enterprise-scale dashboards, reports, and executive-level data visualizations.
• Experience working with modern cloud-based data platforms and enterprise data ecosystems.
• Demonstrated experience integrating data from multiple systems using APIs, REST services, ETL/ELT processes, or other data integration methods.
• Strong understanding of dimensional data modeling, data warehousing principles, and analytical data architecture.
• Proven ability to translate complex business requirements into scalable technical solutions and actionable analytics.
• Excellent written and verbal communication skills, including the ability to present technical concepts to executive and non-technical audiences.
• Experience partnering directly with senior leadership, business stakeholders, and cross-functional teams to define analytics strategy and deliver business value.
• Experience collaborating with infrastructure, security, and application teams to establish secure access to enterprise systems, integrate data from multiple sources, and deliver end-to-end analytics solutions.

Preferred Experience

• Experience with one or more of the following technologies or platforms: Tableau, Next Tableau, Snowflake, Databricks, Microsoft Fabric, Power BI, Salesforce Data Cloud, Microsoft Azure, Amazon Web Services (AWS), Python, Git, dbt.
• Experience with modern artificial intelligence and advanced analytics technologies, including: AI copilots and generative AI tools, Large Language Models (LLMs), Prompt engineering techniques, Retrieval-Augmented Generation (RAG) architectures, Agentic AI workflows, and intelligent automation.
• Machine learning concepts and foundational predictive analytics.

Duties

• Understand the Business: Partner directly with executive leadership and business stakeholders to understand strategic objectives and translate business needs into scalable analytics solutions.
• Establish Access: Collaborate with infrastructure, security, and application teams to establish secure access to enterprise systems and data sources.
• Build the E2E Solution: Design, develop, and maintain end-to-end analytics solutions, including data ingestion, integration, transformation, semantic modeling, visualization, and executive reporting.
• Engineer the Integrations and Data Movement: Design, build, and maintain secure data integrations, automated data exchanges, data synchronization workflows, and enterprise data relays between business systems using APIs, connectors, cloud services, and other integration technologies.
• Integrate Enterprise Systems: Integrate and manage data across Salesforce, Workday, Acumatica, Microsoft 365, SharePoint, cloud data platforms, and other enterprise applications.
• Model the Data: Build scalable semantic data models and reusable datasets that promote consistency, governance, and enterprise-wide reuse.
• Automate Pipelines: Develop and maintain automated data pipelines, reporting workflows, and orchestration processes to improve efficiency, reliability, and delivery speed.
• Deliver Analytics: Design and deliver executive dashboards, operational reporting, and self-service analytics solutions that drive informed decision-making.
• Deploy to Digital Displays: Own the publication, deployment, and ongoing operation of executive dashboards and analytics content across web, mobile, and enterprise digital display environments, ensuring information is accurate, current, and reliably displayed to business stakeholders.
• Apply AI: Evaluate, implement, and optimize AI-assisted analytics capabilities, including copilots, large language models (LLMs), prompt engineering, and intelligent workflow automation where appropriate.
• Optimize: Monitor and optimize solution performance, data quality, reliability, and governance across the analytics ecosystem.
• Enable User Adoption: Provide technical leadership and mentorship to team members while enabling business users through self-service analytics, training, and adoption of enterprise reporting standards and analytics engineering best practices.
• Continuous Improvement: Continuously evaluate emerging analytics technologies and identify opportunities to automate processes, reduce manual effort, and improve analytics capabilities.

Other Responsibilities

• Perform other job duties as assigned.