As a Data Analyst at Cognizant, you will play a critical role in transforming complex datasets into actionable insights for an international organization. You will design efficient reporting solutions, optimize data workflows, and support strategic decisions across business units.
Cognizant is a leading global professional services company, transforming clients' business, operating and technology models for the digital era. With over 340,000 employees worldwide, Cognizant is a Fortune 200 company and is consistently ranked among the most admired companies in the world.
Why required: Python is required for data analysis, including data manipulation, statistical exploration, and integration with visualization and reporting tools.
How recruiters evaluate: The recruiter will evaluate your proficiency in Python, including your ability to write efficient code, work with data structures, and integrate with other tools.
Why required: Excel is required for advanced data analysis, including data modeling, data visualization, and reporting.
How recruiters evaluate: The recruiter will evaluate your expertise in Excel, including your ability to create complex formulas, pivot tables, and charts.
Why required: VBA is required for automating repetitive tasks, improving data accuracy, and reducing manual processing time.
How recruiters evaluate: The recruiter will evaluate your experience with VBA, including your ability to write macros, work with objects, and debug code.
Why required: Tableau is required for data visualization and reporting, including creating interactive dashboards and visual analytics.
How recruiters evaluate: The recruiter will evaluate your experience with Tableau, including your ability to create dashboards, work with data sources, and publish reports.
Why required: Power BI is required for business intelligence and data analysis, including creating reports, dashboards, and data models.
How recruiters evaluate: The recruiter will evaluate your experience with Power BI, including your ability to create reports, work with data models, and publish dashboards.
Why required: Data analysis is required for transforming complex datasets into actionable insights, including data profiling, feature exploration, and visual techniques.
How recruiters evaluate: The recruiter will evaluate your experience with data analysis, including your ability to work with data structures, apply statistical techniques, and communicate insights.
Freshers with a degree in Computer Science, Statistics, or Mathematics can apply for this role.
Experienced professionals with a background in data analysis, business intelligence, or data science can apply for this role.
Graduates with a degree in Computer Science, Statistics, or Mathematics can apply for this role.
B.Tech graduates with a degree in Computer Science, Information Technology, or related fields can apply for this role.
MCA graduates with a degree in Computer Applications can apply for this role.
Diploma holders with a degree in Computer Science, Information Technology, or related fields can apply for this role.
The average salary for a Data Analyst in India is ₹6-12 lakhs per annum.
Freshers can expect a salary range of ₹4-8 lakhs per annum.
Experienced professionals can expect a salary range of ₹10-20 lakhs per annum.
Salaries can vary based on location, experience, and industry.
With experience, you can move into a senior role, leading projects and teams.
With advanced skills and experience, you can move into a data scientist role, working on complex projects and developing predictive models.
With leadership skills and experience, you can move into a management role, overseeing business intelligence initiatives and teams.
Develops technical skills and experience with Python.
Develops technical skills and experience with Excel.
Develops technical skills and experience with Tableau.
To succeed in this role, focus on developing technical skills, staying up-to-date with industry trends, and building strong communication and teamwork skills.
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Data Analyst
00069824501
Date published
Jul 30 2026
Location
Bangalore / India
Job category
Technology & Engineering
Work model
Hybrid
Job Summary
This hybrid role for an experienced data analyst involves using Python Excel VBA macros Tableau Power BI and exploratory data analysis to transform complex datasets into actionable insights for an international organization. The analyst will design efficient reporting solutions optimize data workflows and support strategic decisions across business units while applying industry essentials knowledge to improve processes and contribute to sustainable growth.
Responsibilities
Analyze complex business datasets using exploratory data analysis techniques to uncover trends patterns and anomalies that directly inform strategic decisions and operational improvements across the organization.
Develop robust data models and analytical frameworks in Python that standardize calculations support predictive insights and enable scalable reuse across teams and projects.
Good experience in Power BI
Design and maintain advanced Excel workbooks and macro driven solutions that automate repetitive tasks improve data accuracy and significantly reduce manual processing time for stakeholders.
Build interactive Tableau dashboards and visual analytics that clearly communicate key performance indicators helping business partners quickly understand results and act on data driven recommendations.
Collaborate with cross functional teams to gather requirements translate business questions into analytical problems and deliver clear outputs that align with enterprise priorities and industry essentials.
Implement rigorous data quality checks using MS Excel Python and other tools to validate sources reconcile discrepancies and ensure decision makers can rely on consistent and accurate information.
Optimize data pipelines and reporting workflows by reviewing existing processes identifying bottlenecks and proposing automation strategies that improve efficiency in a hybrid work environment.
Document analytical methods datasets assumptions and business rules in a detailed yet accessible manner to support transparency reproducibility and onboarding of new team members.
Provide actionable insights through well structured reports and presentations that highlight business impact quantify opportunities and support continuous improvement across day shift operations.
Partner with stakeholders to perform scenario analyses and what if assessments using Excel VBA and Python models evaluating potential outcomes and supporting risk aware planning.
Apply industry essentials knowledge to benchmark performance interpret external trends and ensure that analytical outputs reflect relevant regulations standards and market dynamics.
Support governance practices by adhering to data security policies respecting privacy considerations and promoting ethical use of analytics that benefits customers communities and the company mission.
Contribute to a culture of analytical excellence by sharing best practices mentoring peers on modern data techniques and championing the use of evidence based decision making in everyday work.
Qualifications
Demonstrate strong proficiency in Python for data analysis including data manipulation statistical exploration and integration with visualization and reporting tools.
Show advanced expertise in MS Excel and Excel macro VBA development to construct automated workflows complex formulas and template driven reporting solutions.
Apply solid experience in Tableau to design user friendly dashboards that transform technical metrics into intuitive visuals tailored to diverse business audiences.
Exhibit deep understanding of exploratory data analysis principles including data profiling feature exploration and visual techniques that reveal meaningful patterns and outliers.
Bring practical domain exposure in industry essentials allowing effective alignment of metrics with business realities regulatory contexts and evolving market expectations.
Operate effectively in a hybrid work model using collaborative platforms to coordinate tasks communicate findings and maintain productivity during onsite and remote work.
