Analytics Engineer

Analytics Engineer

Role Summary

What This Role Owns

• Dashboard design and visual analytics standards.
• Certified analytics products and executive KPI dashboards.
• Databricks AI/BI dashboard development and analytics user experience.
• Dashboard rationalization and modernization from legacy BI tools.
• Analytics adoption, feedback loops, and usability improvements.
• Coaching business analysts and power users on visualization quality, dashboard performance, and data storytelling.
• Partnership with the Director of Data Enablement on semantic layer usage, KPI consistency, and certified dataset adoption.

Partnership Boundary

Certified Analytics Product Development

• Design, build, and maintain dashboards and analytics products using governed and certified datasets.
• Create executive-caliber dashboards that are clear, accurate, actionable, and visually consistent.
• Translate ambiguous business questions into analytical requirements, dashboard designs, and decision-support products.
• Partner with Finance, Commercial, Operations, Customer Experience, and leadership teams to ensure analytics products answer real business questions.

Databricks Analytics Modernization

• Support the transition from Tableau-centered reporting to Databricks-native analytics capabilities.
• Build and maintain Databricks AI/BI dashboards and related analytics assets.
• Help rationalize existing dashboards and reports, identifying what should be migrated, redesigned, consolidated, retired, or rebuilt.
• Support governed self-service analytics by designing intuitive, trusted, and well-documented analytics experiences.

Executive KPI and Dashboard Modernization

• Build trusted executive KPI dashboards aligned to certified business definitions.
• Ensure filters, calculations, dimensions, hierarchies, and business definitions are consistent across analytics products.
• Partner with the Director of Data Enablement and domain owners to ensure KPI definitions are clear, approved, and usable.
• Help reduce conflicting reports, spreadsheet shadow marts, and “my number is different” conversations.

Visualization Standards and Analytics UX

• Establish and maintain dashboard design standards, UX patterns, naming conventions, taxonomy, and data storytelling principles.
• Improve dashboard usability, clarity, performance, and adoption.
• Design dashboards that help users see what matters quickly, understand context, and take action.
• Apply strong judgment around when a dashboard, scorecard, table, narrative insight, or exception-based workflow is the right solution.

Business Analyst and Power User Enablement

• Serve as a center-of-excellence partner for business analysts and power users.
• Coach users on dashboard design, visual clarity, performance, and appropriate use of certified datasets.
• Support training and adoption activities tied to the Data Modernization & AI program.
• Capture feedback from business users and help prioritize improvements with the Director of Data Enablement.

Priority Use Case Support

• Executive KPI and certified dashboard modernization: trusted dashboards aligned to certified definitions and governed datasets.
• Fully-loaded profitability analysis: scalable frameworks that trace sales through supply chain history to surface true pocket profitability across freight, warehousing, financing, and disposal costs — building on existing analytical work toward a governed, continuously updated model.
• Strategic pricing and margin leakage: visual decision tools for margin risk, price realization, and leakage analysis.
• FPL / supplier price-change analysis: dashboards and exception views that support review of supplier cost changes.
• Order remark classification / Esker touchless order progress: analytics that track classification accuracy, exception volumes, automation opportunities, and operational impact.

First 12-18 Month Success Outcomes

• Executive KPI dashboard modernization underway or delivered using governed datasets.
• Legacy Tableau/dashboard inventory rationalized with clear migration, retirement, or redesign decisions.
• Databricks analytics standards established for dashboard design, naming, filters, KPI display, and user experience.
• Certified analytics products adopted by priority business teams.
• Business analysts and power users actively using standards, templates, and guidance.
• Measurable reduction in duplicative reports, conflicting definitions, or manual reporting work.

Required Qualifications

• 5+ years of experience designing and delivering dashboards, analytics products, or business intelligence solutions.
• Strong SQL skills and ability to work with modeled datasets, semantic layers, and analytical views.
• Demonstrated ability to translate complex business questions into clear analytical outputs.
• Strong data visualization, UX, and data storytelling skills.
• Experience working with enterprise data from ERP, CRM, finance, sales, operations, or similar business systems.
• Ability to collaborate across technical and non-technical stakeholders.
• Strong communication skills and ability to explain analytical concepts without unnecessary jargon.

Preferred Qualifications

• Certification in or experience with Databricks AI/BI, Databricks dashboards, Genie, or similar modern analytics platforms.
• Experience with Tableau, Power BI, Looker, Sigma, ThoughtSpot, or similar BI tools.
• Experience migrating, rationalizing, or modernizing legacy dashboard environments.
• Familiarity with certified datasets, semantic layers, metric governance, and data catalogs.
• Experience in B2B distribution, specialty chemicals, ingredients, manufacturing, or regulated business environments.
• Exposure to AI-assisted analytics, natural-language querying, or narrative insights.

Working Style

• Strong visual thinker with practical business judgment.
• Comfortable challenging unclear reporting requests and helping stakeholders define the real decision they need to make.
• Bias toward simplicity, consistency, and usability.
• Collaborative partner to IT, Data Enablement, business analysts, and functional leaders.
• Able to balance executive polish with operational usefulness.
• Focused on adoption and trust, not dashboard volume.