Data Analyst applicants have rated the interview process at SAP with 2.7 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 67% positive. To compare, the company-average is 70.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Analyst roles take an average of 17 days to get hired, when considering 3 user submitted interviews for this role. To compare, the hiring process at SAP overall takes an average of 28 days.
Common stages of the interview process at SAP as a Data Analyst according to 3 Glassdoor interviews include:
Phone interview: 23%
Skills test: 23%
One on one interview: 15%
Background check: 15%
Personality test: 15%
Group panel interview: 8%
Here are the most commonly searched roles for interview reports -
I applied online. The process took 1+ week. I interviewed at SAP (Prague) in May 2024
Interview
It was very smooth. I started to explain myself first. Then , they asked me questions about the position and my background knowledge. i explained the questions. Then, Hr explained the company and position that i applied
Interview questions [1]
Question 1
HR asked me to that what was your motivation to choose this company and job position?
do you have any project about data analysis?
what was the most challenging part in this project?
how did you handle this challenges and learn from this challenge?
Interview experience was average. Interviewers were very cooperative.
However, the set of questions were a little tricky. There were three rounds, 2 technical and 1 HR. First round mainly focused on projects mentioned in the resume while second round was based on database and cloud.
I applied, and they selected candidates according to education, skills, and enthusiasm.then they call for interview. They ask some depth question regarding data cleaning and vartualization ,i did it .
I applied through college or university. The process took 4 days. I interviewed at SAP (Bangalore Rural) in Jul 2024
Interview
Analyzed sales data of a pizza store using SQL queries to extract KPIs such as revenue, top-selling items, and order trends.
Built a Power BI dashboard with interactive visuals showing daily and hourly trends, category-wise sales, and product performance.
Enabled business insights for decision-making by integrating clean CSV data with structured queries and visual storytelling.
Interview questions [1]
Question 1
Analyzed sales data of a pizza store using SQL queries to extract KPIs such as revenue, top-selling items, and order trends.
Built a Power BI dashboard with interactive visuals showing daily and hourly trends, category-wise sales, and product performance.
Enabled business insights for decision-making by integrating clean CSV data with structured queries and visual storytelling.