Data Visualization Engineer – Consumer Insights
Title: Data Visualization Engineer — Consumer Insights
Employment Type: Contract (W2) | Part-time
Location: Remote
Duration: 6 months (ASAP — 03/31/2026)
Hours: 20 hours/week (flexible across 5 days)
Max Rate: $190/hr (USD)
The Difference You Will Make
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
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Lead implementation and integration of data visualization software, including tool selection.
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Guide planning and adoption of a new dashboard environment.
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Integrate third-party data sources into internal analytics platforms (Tableau or equivalent).
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Design and develop interactive dashboards (Tableau, Power BI, Looker, etc.) with data tables and visualizations for researchers and marketers.
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Optimize dashboards for usability, performance, and accessibility.
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Iterate and refine dashboards based on feedback and evolving data.
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Provide training and documentation to help users interpret and interact with dashboards.
Qualifications
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Data Visualization (5 years): Demonstrable expertise designing scalable dashboards and visual analytics solutions using Tableau, Power BI, Looker, or equivalent platforms.
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Data Integration & Pipelines: Strong experience integrating third-party data (APIs, AWS S3, Snowflake, etc.) into analytics platforms; ability to build automated ETL workflows.
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Data Transformation & Modeling: Advanced SQL and data modeling skills; ability to transform structured/unstructured data into analysis-ready formats.
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Visualization Frameworks: Familiarity with enterprise visualization systems (e.g., Tableau live/extract, Superset, Power BI self-service).
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Insights Generation: Skilled in distilling complex datasets into actionable insights with intuitive UI/UX dashboard design.
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Large-Scale Data Handling: Experience with complex, high-volume datasets (marketing research, consumer behavior, operational metrics). Familiarity with statistical or predictive modeling a plus.