Data Analyst at Amazon- 7 Excellent Ways to be one!

Introduction to Data Analyst at Amazon

“Without big data analytics, companies are blind and deaf, wandering out onto a weblike deer on the freeway.” -Geoffery Moore 

Over a period of a decade, the meaning of data has been completely changed. What type of content are we inhibiting through social media? What are we shopping for? What are we searching for on the web? Has become the data. And to be exact, every activity on the web has become data. This data acquires our likes and interests, and companies use this to gather our attention for their benefits. 

Companies hire data analysts for this. The ability of businesses—large and small—to extract valuable insights from the vast amounts of data they deal with is crucial. Data analyst at amazon do just that. They analyze statistical data and transform it into informative data that businesses and organizations may use to make important decisions.

Let us discuss some of the important facts about Amazon. In this era of big data, Amazon tracks every consumer click and interaction on its website, including what products customers are viewing, what products they add to their shopping cart, what kind of products they prefer, etc.

By gathering this information and feeding it into its recommendation engine, Amazon is able to better meet the demands of its consumers and enhance the shopping experience by suggesting goods that are most in line with their interests. Data is used by Amazon to make business choices and encourage growth. The correct analysis is built by data analysts at Amazon in collaboration with both technical and non-technical internal teams to address important business challenges.

Being a gigantic conglomerate of all time, Amazon usually needs a team of liable and intelligent data scientists. 

As a result, data analysts are sought after by the largest organizations in the world, making data analysis one of the professions with the highest demand worldwide. The need for this employment type, which is expected to continue expanding rapidly, is reflected in the compensation and benefits offered to data analysts.

Therefore, it would be negligent of you to pass up this opportunity if you possess the abilities necessary to work as a data analyst. Let’s look at all the components of this job function in this article on “data analyst at amazon” before delving into a data analyst job description in detail.

Data Analyst VS Business Analyst

Data analysts and business analysts perform comparable functions, and some businesses may use the terms interchangeably. Both sorts of analysts use data to improve business decisions, but in different ways.

Data Analysts collect, clean, analyze, visualize, and present existing data to aid in the decision-making process. A successful data analyst analyzes data to answer questions and empowers decision makers to determine the best course of action.

Business analysts assist firms in identifying challenges, opportunities, and solutions. They accomplish this by:

• Assessing the current roles and IT systems of an company
• Examining processes and conducting interviews with team members to find opportunities for improvement
• Management and other important stakeholders will be informed of the results and recommendations.
• Developing graphics and financial models to assist with business decisions 
• Staff training and coaching in new systems

Data Analyst at Amazon Job Role

Data analysts at Amazon assist in bridging the information-decisions gap. Typically, Data Analyst at amazon jobs include metric definition and review, dashboard or report design, and data analysis. Systems for data collection, compilation, analysis, and reporting are also designed by data analysts at Amazon.com.

The sort of data analyst at amazon works with (such as data from Twitch, sales, Alexa, etc.), the project they are working on, the product they are working with, and the team they are assigned to all have different functions. To offer data-driven insights into research and business areas, data analysts at Amazon also work cross-functionally with a variety of teams, including engineering, data science, and marketing.

The function could involve anything from straightforward business intelligence analytics like data processing, analysis, and reporting to a more technical role like data collection, depending on the team.

The roles of data analysts at Amazon can vary depending on the team.

• Alliance (Twitch): Using advanced analytics to define what questions should be asked, how deal performance should be monitored, and scale analytics techniques and tools to support Twitch’s expanding business. Defining and monitoring KPIs, supporting strategic goals, assessing new business prospects, and enhancing or improving decision-making using data are other important tasks.
• Develop standard and ad hoc analysis and reports for financial operation decision-making. High-level business issues should be organized around data analysis, definition, creation, sourcing, metric production, and suggestion making. Driving data governance and uniformity while automating standard reporting
• Utilize cutting-edge analytics and predictive algorithms to develop effective, user-centered search solutions and technologies. Working together with the engineering and operations teams, establish and monitor KPIs for efficiency and cost in order to scale the Amazon search service.
• Text book group: Create reliable data analytics programs to enhance the consumer experience. Analytics, data modeling, and sophisticated data mining techniques can be used to develop and measure the metrics that will be used to gauge corporate growth. To create data pipelines, automate reports and dashboards, and make use of self-service solutions for internal stakeholders, it is necessary to extract, integrate, and operate on vital data.
• Purchasing: Calculate how much inventory to keep on hand across all of Amazon’s international websites using advanced analytics techniques. Create and maintain metrics, reveal and assess the performance of Amazon’s purchasing system as it is, pinpoint and quantify areas for improvement, and make use of Amazon’s enormous data set to spot and avoid unexpected performance. For future innovation, work cross-functionally with other teams, especially those in engineering, research, data science, and business.
• Engineering Success : In order to support Amazon’s expanding company, work with the Twitch engineering team to deliver data analysis for enhancing and defining success measurement measures, establishing business-impact questions, and scaling analytics methodologies and tools.

Read Also: Amazon Data Scientist  

Data Analyst at Amazon – Basic & Skill Requirements

The job of data analyst at Amazon calls for specialized training and experience. Because of this, Amazon exclusively employs highly skilled applicants with at least three years of relevant experience in domains like advanced business analytics, data analysis, and data modeling.

Additional prerequisites for data analyst at Amazon include:

• A bachelor’s or master’s degree in finance, business, economics, engineering, mathematics, statistics, computer science, operations research, or a related discipline is required (a doctorate is desirable).
• Having knowledge of data warehousing tools like Linux, R, SAS, and/or SQL, as well as scripting and querying
• Extensive knowledge in coding languages like Java, R, or Python.
• SQL querying expertise as well as practical processing, optimization, and analysis knowledge with huge data sets.
• Proficiency with Access, Macros, and Microsoft Excel.
• Having knowledge of measurements and KPIs, data collection, experimentation, and the presentation of scorecards, dashboards, and presentations.
• Knowledge of automated self-service reporting and business intelligence solutions like Tableau, Quicksight, Microsoft Power BI, or Cognos
• Knowledge of AWS services like Lambda, SQS, or RDS.

Data Analyst at Amazon – Interview Process

At Amazon, the hiring procedure for a data analyst at amazon is comparable to that at other tech firms. The Amazon interview process includes an initial phone interview, a technical phone screen, a behavioral phone screen, and a final in-person interview.

The organization evaluates a candidate’s familiarity with programming languages including Python, Java, and SQL through the technical interview process. It guarantees that a candidate is well-versed in statistics, math, data mining, data extraction, and the entire data pipeline. Additionally, it evaluates the candidate’s proficiency using tools for data visualization and machine learning.

The organization wants to learn more about a candidate through behavioral screening in order to assess their communication abilities, evaluate their problem-solving techniques, and witness examples of the 14 leadership principles.

These are the most common topics discussed at data analyst at amazon interviews.

There are 3 stages of the interview process for the position of data analyst at Amazon: 

• Stage- 1: Recruiter’s Call/ HR Round
• Stage- 2: Technical Round 
• Stage-3: On-Site Round

Stage- 1: Recruiter’s Call/ HR Round

The first meeting with Amazon is a 30-minute recruiter screening aimed at assessing the candidate’s role-fit, culture-fit, and logistics.

Prior to the call:

In the applicant tracking system (ATS), the recruiter sees your job application, which includes a resume and optional cover letter. Your application is ranked algorithmically depending on how closely your qualifications match the job descriptions. Recruiters will usually contact applicants with the highest ranking first.

During the call of Data Analyst at Amazon Interview:

The recruiter will structure the meeting in the following manner during the call, which will last roughly 20 to 30 minutes:

• Introduction: The recruiter will go through the role expectations and team in further depth.

• Background information for candidates: This is your chance to tell us about yourself. “Tell me about yourself,” the recruiter will inquire. You can give a high-level overview of your academic and professional backgrounds. “Why do you want to work as data analyst at Amazon?” is one of the follow-up inquiries.

• The recruiter will normally inquire about the following: What city are you in? What are your technical interview availability?

• Follow-Ups – The recruiter will outline the following steps, including when you should expect to hear back and how to prepare for technical rounds. This is your opportunity to ask as many questions as possible in order to plan out the technical interviews from beginning to conclusion. The more information you have, the better prepared you will be for interviews.

After the call: 

Following the call, the recruiter will contact the hiring manager with remarks on the candidate’s background, technical screening, logistics, and cultural fit. The recruiter and hiring manager will move you to the first technical round for data analyst at Amazon if they believe you have promise.

Stage- 2: Technical Round for Data Analyst at Amazon

This is a technical interview with an HR representative or a manager. For all technical interviews, Amazon employs a collaboration service platform called “CollabEdit.”

This interview round’s questions for a data analyst at Amazon revolves around SQL coding challenge, Excel, and questions about Amazon’s Leadership Principles (LP). Practicing the Amazon SQL questions on Interview Query is definitely beneficial.

Stage-3: On-Site Round for Data Analyst at Amazon

The onsite interview for a data analyst at Amazon is very similar to the company’s other onsite interviews. Candidates who advance to this stage of the interview process will be interviewed one-on-one by a hiring manager, a team manager, data analysts, data engineers, and statisticians.

In between interview rounds, there is a lunch break. The onsite interview rounds for data analyst at amazons include data science concepts, SQL coding, and the well-known Amazon Leadership Principles.

Also Read: Amazon Data Scientist Interview Process   

Questions for Data Analyst at Amazon Interview

• Which SQL functions are your favorites?
• Explain OLAP cubes and a business analytics application use case.
• What is the difference between data normalization and non-normalization?
• When the associated table with primary keys is updated, what happens to the data in the table with foreign keys?
• What exactly do you mean by cascading referential integrity?
• Use examples to explain the difference between linear and logistic regression.
• What is an independent variable, and what if my model contains three independent variables but no dependent variable?
• Create an equation for the multiple regression or multivariate model.
• How would you test a hypothesis given a sample of n observations?
• What are the ANOVA assumptions?
• What method would you use to test a small sample?
• What exactly is the null hypothesis?
• What are the differences between type 1 and type 2 errors?
• Create a query using the tables below to retrieve data for customers who registered within the last ten days and spent more than $100. Create another query to retrieve information for customers who spent more than $100 in the previous seven days. The first table contains five columns: customer id, purchase date, product id, unit price, and units purchased. The second table contains two columns: the customer id and the registration date.
• What is the chance of getting ten consecutive numbers in ascending order out of 100?
• In SQL, how would you merge two tables?
• In any of these languages, write a function to calculate the Fibonacci sequence (VBA, Python, Java).

Data Analyst at Amazon Salary in India

A data analyst at Amazon with 1 – 4 years of experience in India can earn up to Rs 3,96,128, while a mid-career Data Analyst with 5 – 9 years of experience can earn up to Rs 6,03,120 depending on the organization and location of the working place. And if you are a matured and experienced Data Analyst with 10 – 19 years of experience, you can earn an average total compensation of Rs 9,00,000.

While 78 percent of analytics professionals in India earn between 0 and 6 lakhs at their entry level, the increase in the number of freshers in Data Analysis in India is a good sign that the industry is maturing. Multiple factors influence Data Analyst at amazon salary in India, including location, skills, experience, and company. Salaries for those with 4 to 6 years of experience remain stable at 8.7 lakhs. Senior Data Analysts with 12 or more years of experience saw a 20 percent increase in salary last year.

Companies all over the world are highly valuing analytics and its potential to change market trends, prompting company decision-makers to invest more and more in technology, people, and processes.

As a result, data analytics has shifted from I.T. and finance to almost all business functions. According to the US Bureau of Labor Statistics, Data Analysts are expected to grow at a faster-than-average rate of 19% from 2014 to 2024, owing to the continuous growth of data generation and the need to refine and extract relevant insights from the same.

Read Also: Google Data Scientist Interview 

Conclusion

From a one-stop-shop to world’s largest e-commerce company, Amazon inculcated a variety of growth strategies and opportunities. One of them is data analysis. No doubt, creating this big customer support can be difficult but when you know what your customers likes and dislikes, it becomes easy to grab their attention. At this process data analytics comes in handy. Becoming a data analyst at Amazon is a dream of many of us.  

Amazon does not only provide great payroll, great working environment and enough bonuses but it also gives newness to data analysis as it is a conglomerate of all time. 

Data Analyst at Amazon should possess important skills such as Tableau, Quicksight, Microsoft Power BI, or Cognos, knowledge of AWS services like Lambda, SQS, or RDS.

Apart from it, a data analyst at amazon need to learn and gather the ideology of 14 Leadership principles provided by Amazon itself.