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Business Intelligence Engineer

Amazon

Chennai, Tamil Nadu, IndiaOn Site

Original Job Summary

Overview

RBS Brand Experience at Amazon is seeking a skilled Business Intelligence Engineer who transforms complex data into actionable insights. You will decipher evolving business needs and create data-driven solutions at a global scale.

Key Responsibilities

  • Develop advanced SQL queries and stored procedures for data extraction and analysis.
  • Utilize Python with libraries such as pandas and PySpark for ETL and data manipulation.
  • Design scalable ETL pipelines and optimize data models.
  • Build and maintain data warehouses, data lakes, and insightful dashboards using BI tools.
  • Collaborate with cross-functional teams to translate business requirements into effective analytics solutions.

A Day in the Life

You will work closely with product managers, software developers, and business stakeholders to build dashboards, perform deep-dive analyses, automate data processes, and present actionable insights to leadership.

Basic Qualifications

  • 2+ years of experience with SQL, data visualization, and ETL processes.
  • Proficiency in Python along with basic scripting skills in Java or R.
  • Experience with databases such as Redshift, Oracle, and NoSQL systems.
  • Familiarity with BI tools like Tableau or Quicksight.

Preferred Qualifications

  • Bachelor's degree or advanced technical degree.
  • Experience in data modeling, statistical methods, and automation for reporting systems.

Key skills/competency

  • SQL
  • Python
  • ETL
  • Data Modeling
  • Data Warehousing
  • BI Tools
  • Data Visualization
  • Dashboard
  • Analytics
  • Problem-solving

How to Get Hired at Amazon

🎯 Tips for Getting Hired

  • Customize your resume: Highlight SQL, Python, ETL, and dashboard skills.
  • Research Amazon: Study its culture and global data initiatives.
  • Prepare for interviews: Focus on technical and analytical problem solving.
  • Showcase projects: Demonstrate relevant data engineering successes.

📝 Interview Preparation Advice

Technical Preparation

Review advanced SQL query techniques.
Practice Python data manipulation with pandas.
Learn ETL pipeline design fundamentals.
Optimize data models using case studies.

Behavioral Questions

Describe a time of solving data ambiguity.
Explain collaboration with cross-functional teams.
Discuss handling multiple data sources.
Share an experience presenting business insights.