Cognizant has a Data Analyst opportunity in Bangalore for candidates interested in data analysis, business intelligence, reporting, and data-driven decision-making.
This role(Cognizant Data Analyst Hiring 2026) is more than simply working with spreadsheets. Data Analysts can work with business datasets, identify trends and issues, prepare reports, build dashboards, and help teams understand what the data is saying.
The available information for this particular opening does not clearly confirm a fresher-only requirement, specific graduation batches, or a fixed salary. So candidates should check the latest Cognizant application page before applying.
Cognizant Data Analyst Hiring 2026 – Job Overview
Field
Details
Company
Cognizant
Role
Data Analyst
Job ID
00069824501
Job Type
Full Time
Location
Bangalore, Karnataka
Work Model
Hybrid
Experience
Not clearly specified as a fixed range
Qualification
Check the current job description
Batch
Not specified
Salary
Not disclosed
Category
Technology & Engineering
The available listing for Job ID 00069824501 identifies Bangalore as the location, a hybrid work model, and Technology & Engineering as the job category.
About Cognizant
Cognizant is a global technology and professional services company working across technology, consulting, business operations, data, cloud, AI, and digital transformation.
For people building a career in analytics, the company has opportunities across different technology and business functions. Cognizant also has dedicated programs for students and new graduates, including its Generation Cognizant program.
What Does a Data Analyst Do?
A Cognizant Data Analyst Hiring 2026 takes raw or business data and turns it into information that teams can actually use.
The work can involve:
Collecting and preparing data.
Cleaning incorrect or incomplete information.
Analysing datasets.
Looking for trends and unusual patterns.
Checking data quality.
Creating reports.
Building dashboards.
Automating repetitive reporting tasks.
Explaining findings to business teams.
For the Cognizant Data Analyst Hiring 2026 opening associated with Job ID 00069824501, available job information points to analytics, reporting, visualization, automation, and business decision support as important parts of the work.
Key Skills Mentioned for This Data Analyst Role
The available listing specifically highlights a combination of analytics and business intelligence skills.
Python
Python can be used for data cleaning, analysis, automation, and working with larger datasets.
For a Cognizant Data Analyst Hiring 2026 role, you should be comfortable with basic data manipulation rather than simply knowing Python syntax.
Useful areas include:
Reading datasets.
Cleaning data.
Filtering and transforming information.
Working with columns and rows.
Automating repetitive tasks.
Performing basic analysis.
Microsoft Excel
Excel remains an important tool for business analytics.
You should be comfortable with:
Formulas.
Sorting and filtering.
Pivot tables.
Data validation.
Lookups.
Charts.
Data cleaning.
Excel VBA and Macros
The available job information also highlights VBA and Excel macros.
These can be used to automate repetitive spreadsheet-based work.
For example, instead of manually preparing the same report every week, a macro can automate part of the process and reduce manual effort.
Tableau
Tableau is used for data visualization and dashboard creation.
For this type of role, it is useful to understand how to turn data into a dashboard that business users can easily understand.
Power BI
Power BI is another important business intelligence and visualization tool mentioned for this Data Analyst position.
Candidates for Cognizant Data Analyst Hiring 2026 role should understand how to:
Connect data sources.
Clean data.
Create visualisations.
Build dashboards.
Present useful business metrics.
The available listing specifically identifies Python, Excel, VBA, Tableau and Power BI among the key technologies for the role.
Exploratory Data Analysis
Exploratory Data Analysis, or EDA, is an important part of working with data.
Before creating a final report, an analyst needs to understand what is actually present in the dataset.
EDA can help you identify:
Missing values.
Duplicate records.
Outliers.
Trends.
Relationships between variables.
Unexpected values.
Data quality problems.
For example, if sales suddenly drop by 40%, an analyst should not immediately assume that the business performed badly.
The first step is to investigate whether the data is complete and whether something changed in the underlying data source.
Data Quality and Validation
A report is only useful if the data behind it is reliable.
Data Analysts therefore need to check whether information is accurate and consistent.
This can include:
Comparing data from different sources.
Finding missing values.
Checking duplicates.
Reconciling differences.
Validating calculations.
Checking unusual values.
Confirming that reports contain the correct information.
The available Cognizant listing specifically highlights data quality and validation as part of the analytics work.
What Kind of Work Can You Expect?
A typical task could look something like this:
A business team gives you a large dataset and asks why a particular metric has changed.
You may need to:
Understand the question → Clean the data → Analyse it → Find the pattern → Build a report/dashboard → Explain the result
So the job requires both technical and business thinking.
Knowing how to use a tool is useful, but you should also understand why you are using it and what the final result means.
Is SQL Required?
SQL is one of the most useful skills for Data Analysts, and learning it is strongly recommended for candidates preparing for analytics roles.
However, SQL should not be presented as a confirmed mandatory requirement for this particular Cognizant listing unless the current official job description explicitly states it.
If you are preparing for Data Analyst jobs generally, focus on:
SELECT.
WHERE.
GROUP BY.
ORDER BY.
JOINs.
CASE statements.
Aggregate functions.
Subqueries.
Window functions.
Is This a Fresher Job?
The CareerLaunch article currently labels this opportunity as a fresher opening.
However, the available job information for the specific Data Analyst position does not provide enough evidence to confidently state that it is fresher-only.
Another listing for Job ID 00069824501 describes the position as an experienced Data Analyst opportunity.
Therefore, candidates should not rely only on the “Freshers” label in the old article.
If you are a fresher, you can still use this job description to prepare for similar Cognizant entry-level analytics opportunities. Cognizant separately confirms that it has programs aimed at students and new graduates.
Qualification
The existing CareerLaunch article mentions a Bachelor’s Degree / Master’s Degree, but the publicly available information for this specific opening does not provide enough evidence to treat that as a confirmed universal requirement.
So:
Qualification: Check the latest official job description.
Candidates should not assume that a particular degree, branch, percentage, or CGPA is required unless it is explicitly mentioned in the current posting.
Batch Eligibility
Batch: Not specified in the available job information.
Do not add a specific passing year such as 2024, 2025, or 2026 unless the current application page explicitly mentions it.
Salary
The salary for this Data Analyst opening is not disclosed in the available job information.
Avoid publishing an estimated package as the confirmed salary.
Salary can vary depending on the position, experience, location, and hiring terms.
Work Location and Work Model
The available listing identifies:
Location: Bangalore, Karnataka Work Model: Hybrid
Candidates should still check the current application page for the latest work arrangement because company policies and individual team requirements can change.
How to Prepare for This Data Analyst Role
If you want to move into data analytics, do not try to learn ten different tools at once.
Start with a strong foundation.
Step 1: Learn Excel Properly
Start with formulas, PivotTables, lookups, charts, data cleaning, and basic reporting.
Once you are comfortable with these, move towards VBA if the role requires it.
Step 2: Learn SQL
Practise querying real datasets.
Do not stop after learning SELECT statements. Learn how to combine tables and answer business questions using SQL.
Step 3: Practise Python for Data Analysis
Focus on practical data work.
Learn how to load, clean, filter, transform, and analyse datasets.
Step 4: Build a Dashboard
Create at least one complete dashboard using Power BI or Tableau.
For example, you could build a:
Sales Performance Dashboard
with:
Total sales.
Monthly sales.
Top products.
Regional performance.
Customer trends.
Growth percentage.
Step 5: Explain Your Findings
This is where many candidates struggle.
Do not just say:
“I created a Power BI dashboard.”
Be able to explain:
What problem did the dashboard solve? What did you find? What action could the business take based on the result?
That shows actual analytical thinking.
What Should You Put on Your Resume?
If you are applying for Data Analyst positions, your resume should show practical work.
Include relevant:
Data analysis projects.
Excel projects.
Python projects.
SQL projects.
Power BI dashboards.
Tableau dashboards.
Internships.
Data-related certifications.
Academic projects involving real datasets.
Instead of simply writing:
“Good knowledge of Python and Excel”
show what you actually used them for.
For example:
“Cleaned and analysed a sales dataset using Python and created a Power BI dashboard to track monthly revenue and regional performance.”
Only use statements that accurately describe your work.
A Good Project for Freshers
If you do not have professional experience, create a project that looks like a real business problem.
For example:
E-commerce Sales Analysis
Use a public dataset containing:
Orders.
Products.
Customers.
Revenue.
Dates.
Locations.
Then:
Clean the data using Python or Excel.
Analyse sales trends.
Find the best-performing products.
Identify underperforming regions.
Create a Power BI or Tableau dashboard.
Write a short summary of your findings.
This gives you something concrete to discuss during an interview.
Questions You Should Be Ready to Answer
For a Data Analyst interview, prepare for questions around your actual skills and projects.
Excel
How does a PivotTable work?
When would you use XLOOKUP?
How would you find duplicate records?
How would you clean a messy spreadsheet?
SQL
What is the difference between INNER JOIN and LEFT JOIN?
How do you find duplicate records?
How do you calculate totals by category?
What are window functions?
Python
How do you handle missing values?
How do you filter a dataset?
What is pandas used for?
How would you identify outliers?
Power BI / Tableau
How did you design your dashboard?
Which metrics did you choose?
How did you clean the data?
What insight did your dashboard provide?
Project
Most importantly, be ready to explain your own project from beginning to end.
Application Status
The CareerLaunch article states that the opportunity was listed on August 5, 2026.
Because job availability can change, candidates should check the current Cognizant careers portal before applying.
Cognizant’s official careers website currently has a large number of active job listings across technology, engineering, analytics, and other functions.
How to Apply for Cognizant Data Analyst Hiring 2026
If the Data Analyst opening is still active, apply through the official Cognizant careers portal or the current application page associated with the job.
Do not pay anyone in exchange for a Cognizant job application, interview, or offer.
Use Cognizant’s official careers channels and verify recruitment communication carefully.
Also, avoid copying a long list of analytics keywords into your resume just to match the job description. If you mention Python, Excel, VBA, Tableau, Power BI, or any other technology, make sure you can explain how you have actually used it.
Final Takeaway
The Cognizant Data Analyst Hiring 2026 opportunity in Bangalore is relevant to candidates interested in data analytics, business intelligence, reporting, and data-driven decision-making.
The available information for the specific opening highlights Python, Excel, VBA, Tableau, Power BI, Exploratory Data Analysis, data quality, reporting, and analytics.
However, the exact fresher eligibility, degree requirement, batch, salary, and selection process should not be assumed from the older CareerLaunch article.
If you are preparing for this type of role, focus on building practical skills and projects rather than simply collecting certificates. A strong combination of Excel + SQL + Python + Power BI/Tableau + analytical thinking can give you a much better foundation for Data Analyst opportunities.
