Tableau Expert for Marketing & E-commerce Dashboards
Budget: ₹1,250 – ₹2,500 INR
We are looking for an experienced Tableau specialist to help us build clear, insightful dashboards from multiple data sources.
\We work with marketing and e-commerce data and need help transforming structured data tables into meaningful, decision-ready visualizations.
Data sources include:
Google platforms (e.g. Google Ads, GA4)
Meta (Facebook/Instagram Ads)
Shopify (sales, revenue, orders, products)
Additional structured data sources (to be shared)
We will provide cleaned data tables, but a large part of this assignment is:
Understanding how the tables relate to each other
Structuring data correctly inside Tableau
Creating intuitive, scalable visualizations and dashboards
This will require a strong analytical thinking, not just plug & play..
Scope of Work
Review and understand provided data tables and schemas
Build Tableau data models (relationships, joins, calculated fields)
Create dashboards for:
Marketing performance (spend, ROAS, CPA, funnels, trends)
Sales & e-commerce performance (revenue, orders, AOV, product trends)
Design clean, professional visualizations (filters, drill-downs, comparisons)
Ensure dashboards are easy to interpret for business users
What We’re Looking For
Proven experience with Tableau (Desktop & dashboards)
Strong understanding of data structures, tables, and relationships
Experience working with marketing + e-commerce data
Ability to translate raw data into clear business insights
Attention to detail in visualization, layout, and usability
Comfortable asking the right questions when data logic needs clarification
Nice to Have
Experience with Google Ads, Meta Ads, or Shopify data specifically
Knowledge of KPIs like ROAS, CAC, AOV, LTV, conversion rates
Experience working with agencies or fast-moving teams
Engagement Details
Project-based to start (with potential for ongoing work)
Remote / async collaboration
Immediate start preferred
To Apply
Please share:
Examples of Tableau dashboards you’ve built
Briefly explain how you usually approach understanding new data tables
Your availability and hourly / project rate
\We work with marketing and e-commerce data and need help transforming structured data tables into meaningful, decision-ready visualizations.
Data sources include:
Google platforms (e.g. Google Ads, GA4)
Meta (Facebook/Instagram Ads)
Shopify (sales, revenue, orders, products)
Additional structured data sources (to be shared)
We will provide cleaned data tables, but a large part of this assignment is:
Understanding how the tables relate to each other
Structuring data correctly inside Tableau
Creating intuitive, scalable visualizations and dashboards
This will require a strong analytical thinking, not just plug & play..
Scope of Work
Review and understand provided data tables and schemas
Build Tableau data models (relationships, joins, calculated fields)
Create dashboards for:
Marketing performance (spend, ROAS, CPA, funnels, trends)
Sales & e-commerce performance (revenue, orders, AOV, product trends)
Design clean, professional visualizations (filters, drill-downs, comparisons)
Ensure dashboards are easy to interpret for business users
What We’re Looking For
Proven experience with Tableau (Desktop & dashboards)
Strong understanding of data structures, tables, and relationships
Experience working with marketing + e-commerce data
Ability to translate raw data into clear business insights
Attention to detail in visualization, layout, and usability
Comfortable asking the right questions when data logic needs clarification
Nice to Have
Experience with Google Ads, Meta Ads, or Shopify data specifically
Knowledge of KPIs like ROAS, CAC, AOV, LTV, conversion rates
Experience working with agencies or fast-moving teams
Engagement Details
Project-based to start (with potential for ongoing work)
Remote / async collaboration
Immediate start preferred
To Apply
Please share:
Examples of Tableau dashboards you’ve built
Briefly explain how you usually approach understanding new data tables
Your availability and hourly / project rate