What are the responsibilities and job description for the Analytics Engineer position at Palmer Holland?
Brief Description
Analytics Engineer
Reports to: Director of Data Enablement | Location: Westlake, OH | Hybrid
Role Summary
The Analytics Product Engineer designs and delivers trusted analytics products that help Palmer Holland make faster, clearer, and more consistent business decisions.
Reporting to the Director of Data Enablement, this role is responsible for dashboard design, visual analytics, certified analytics products, analytics user experience, and adoption of governed data products across the organization. The role will help modernize Palmer Holland analytics as the company transitions from Tableau-centered reporting toward Databricks-native analytics, certified datasets, and governed self-service capabilities.
This role is not a traditional report writer. It combines business acumen, visualization craft, SQL fluency, semantic understanding, and product thinking to turn governed data into decision-ready analytics experiences.
What This Role Owns
This role partners closely with IT and Data Enablement colleagues but does not own Databricks infrastructure or platform engineering, data pipeline operations, enterprise integrations, security architecture, identity/access management, CI/CD infrastructure, release frameworks, ERP/CRM systems of record, or advanced AI model development as a primary responsibility.
Key Responsibilities
Certified Analytics Product Development
Analytics Engineer
Reports to: Director of Data Enablement | Location: Westlake, OH | Hybrid
Role Summary
The Analytics Product Engineer designs and delivers trusted analytics products that help Palmer Holland make faster, clearer, and more consistent business decisions.
Reporting to the Director of Data Enablement, this role is responsible for dashboard design, visual analytics, certified analytics products, analytics user experience, and adoption of governed data products across the organization. The role will help modernize Palmer Holland analytics as the company transitions from Tableau-centered reporting toward Databricks-native analytics, certified datasets, and governed self-service capabilities.
This role is not a traditional report writer. It combines business acumen, visualization craft, SQL fluency, semantic understanding, and product thinking to turn governed data into decision-ready analytics experiences.
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.
This role partners closely with IT and Data Enablement colleagues but does not own Databricks infrastructure or platform engineering, data pipeline operations, enterprise integrations, security architecture, identity/access management, CI/CD infrastructure, release frameworks, ERP/CRM systems of record, or advanced AI model development as a primary responsibility.
Key Responsibilities
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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.