Website ADA Digital analytic
Senior Data Analyst – ADA Digital Analytics
Opportunity Overview
Digital Analytics & Client Engagement Workflow
The Senior Data Analyst at ADA leads end-to-end client analytics projects—from initial business requirements gathering to extracting insights from structured/unstructured datasets and delivering executive presentations:
┌───────────────────────────────────────────┐
│ 1. Requirements & Stakeholder Alignment │ ➔ Collaborate with clients & internal teams to define analytical objectives
└─────────────────────┬─────────────────────┘
▼
┌───────────────────────────────────────────┐
│ 2. Data Extraction & Pipeline Scripting │ ➔ Execute complex SQL queries & Python scripts across structured & unstructured data
└─────────────────────┬─────────────────────┘
▼
┌───────────────────────────────────────────┐
│ 3. Advanced Analysis & Visualization │ ➔ Perform trend/pattern analysis and build Power BI / Tableau client dashboards
└─────────────────────┬─────────────────────┘
▼
┌───────────────────────────────────────────┐
│ 4. Insight Delivery & Strategic Value │ ➔ Translate technical insights into actionable recommendations for business growth
└───────────────────────────────────────────┘
Key Responsibilities
-
Complex Data Analysis: Extract, clean, and model large structured and unstructured datasets to identify patterns, business trends, and digital growth opportunities.
-
SQL Query Optimization: Write efficient, scalable SQL code for complex data extraction, transformation, and database joins across multi-market client systems.
-
BI Dashboard Architecture: Design, deploy, and maintain interactive client-facing dashboards using Power BI or Tableau.
-
Python Scripting & Automation: Utilize Python for advanced data manipulation, automated reporting tasks, and statistical analytics.
-
Stakeholder & Client Management: Translate “data speak” into strategic recommendations and present findings directly to external enterprise clients and leadership.
Qualification Matrix & Technical Skill Stack
Core Requirements
Key Focus Areas for Interview Preparation
-
Client Analytics Case Studies: Prepare examples where you translated ambiguous business questions from clients into concrete analytical frameworks.
-
Advanced SQL & Python Live Coding: Practice writing optimized SQL queries and Python data manipulation scripts handling messy, unnormalized datasets.
-
Data Storytelling & Visualization: Be ready to showcase past Power BI or Tableau portfolio dashboards, explaining design choices, data modeling, and business impacts.


Follow Us