Data Visualization Engineer

As a Data Visualization Engineer – Consumer Insights, you will transform complex marketing research output from a global tracking study into a network of intuitive dashboards. Your work will make critical data more accessible, digestible, and actionable for cross-functional teams.

You will integrate third-party data sources into internal systems, design interactive dashboards, and provide data tables and visualizations that empower teams to query, track, and measure their KPIs.

This is a temporary, project-focused role (approx. 6 months, 20 hrs/week) dedicated to completing data source integration, dashboard network development, rollout, and iterative improvements.

Responsibilities:

• Lead implementation and integration of data visualization software, including tool selection.
• Guide planning and adoption of a new dashboard environment.
• Integrate third-party data sources into internal analytics platforms (Tableau or equivalent).
• Design and develop interactive dashboards (Tableau, Power BI, Looker, etc.) with data tables and visualizations for researchers and marketers.
• Optimize dashboards for usability, performance, and accessibility.
• Iterate and refine dashboards based on feedback and evolving data.
• Provide training and documentation to help users interpret and interact with dashboards.

Qualifications:

• Data Visualization (5+ years): Demonstrable expertise designing scalable dashboards and visual analytics solutions using Tableau, Power BI, Looker, or equivalent platforms.
• Data Integration & Pipelines: Strong experience integrating third-party data (APIs, AWS S3, Snowflake, etc.) into analytics platforms; ability to build automated ETL workflows.
• Data Transformation & Modeling: Advanced SQL and data modeling skills; ability to transform structured/unstructured data into analysis-ready formats.
• Visualization Frameworks: Familiarity with enterprise visualization systems (e.g., Tableau live/extract, Superset, Power BI self-service).
• Insights Generation: Skilled in distilling complex datasets into actionable insights with intuitive UI/UX dashboard design.
• Large-Scale Data Handling: Experience with complex, high-volume datasets (marketing research, consumer behavior, operational metrics). Familiarity with statistical or predictive modeling a plus.