📍 Job Overview

Job Title: Database Analyst
Company: Experian
Location: Hyderabad, Telangana, India
Job Type: Full-time, On-site
Category: Data & Analytics
Date Posted: June 26, 2025
Experience Level: 10+ years

🚀 Role Summary

Develop and maintain client-facing reports using Business Intelligence tools, with a focus on Sigma and Tableau.
Perform data profiling, troubleshoot data issues, and conduct detailed data analyses using SQL and Python.
Collaborate with cross-functional teams, including engineering, to discover and leverage data, and deliver cross-functional reporting solutions.
Provide on-call production support and maintain report specifications and process documentations.

📝 Enhancement Note: This role requires a strong background in Business Intelligence, with a focus on Sigma and Tableau. Experience with AWS data ecosystem, Python, and working in an Agile environment is also crucial for success in this position.

💻 Primary Responsibilities

Report Development & Maintenance:
- Develop and maintain client-facing standardized reports using Sigma and Tableau.
- Create and update report specifications and process documentations.
Data Analysis & Troubleshooting:
- Perform data profiling on source data with minimal documentation.
- Independently troubleshoot data issues, perform detail data analyses, and develop complex SQL code.
- Write secure, stable, testable, and maintainable Python code with minimal defects.
Collaboration & Problem-Solving:
- Collaborate with engineering teams to discover and leverage data being introduced into the environment.
- Serve as a liaison with business and technical teams to achieve project objectives, delivering cross-functional reporting solutions.
- Perform root cause analysis, propose solutions, and take ownership of the next steps for their resolution.

📝 Enhancement Note: This role requires a high level of independence and the ability to multitask and prioritize an evolving workload in a fast-paced environment.

🎓 Skills & Qualifications

Education: BS degree or higher in MIS or engineering fields

Experience:

Minimum 7 years of experience in BI visualization development and support
2 years of experience in Sigma report development and support
2 years of experience in Tableau Server administration
3 years of experience with AWS data ecosystem (Redshift, S3, etc.)
2 years of experience with Python
3 years of experience in an Agile environment

Required Skills:

Excellent customer-facing communication skills between business partners and technical teams
Highly motivated self-starter, detail-oriented, and able to work independently to formulate innovative solutions

Preferred Skills:

Experience with MWAA and Business Objects
Familiarity with root cause analysis techniques and data-driven problem-solving

📝 Enhancement Note: While not explicitly stated, experience with data visualization libraries (e.g., D3.js, Plotly) and ETL tools (e.g., Talend, Pentaho) could be beneficial for this role.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate experience in developing and maintaining client-facing reports using Sigma and Tableau.
Showcase data analysis and troubleshooting skills through case studies or projects.
Highlight collaboration and problem-solving abilities through cross-functional project examples.

Technical Documentation:

Provide examples of report specifications and process documentations created for previous projects.
Demonstrate familiarity with version control systems (e.g., Git) and data management best practices.

📝 Enhancement Note: As this role involves working with sensitive data, it's essential to include examples of secure coding practices and data protection measures in your portfolio.

💵 Compensation & Benefits

Salary Range: INR 1,200,000 - 1,800,000 per annum (Estimated based on industry standards for a senior-level data analyst role in Hyderabad)

Benefits:

Competitive compensation and benefits package
Opportunities for professional development and growth
A diverse and inclusive work environment
Flexible work arrangements and remote work options (as applicable)

Working Hours: Full-time, with on-call production support as required

📝 Enhancement Note: The salary range provided is an estimate based on market research for similar roles in the Hyderabad area. Experian's benefits package is competitive and includes health insurance, retirement plans, and other perks.

🎯 Team & Company Context

🏢 Company Culture

Industry: Experian operates in the data and technology sector, focusing on powering opportunities for people and businesses worldwide. They specialize in data-driven solutions for various industries, including financial services, healthcare, automotive, agribusiness, insurance, and more.

Company Size: Experian is a large, global organization with a team of 22,500 people across 32 countries. Their corporate headquarters are in Dublin, Ireland.

Founded: Experian was founded in 1960 and has since grown into a FTSE 100 Index company listed on the London Stock Exchange (EXPN).

Team Structure:

Experian's data and analytics teams consist of data analysts, data scientists, and data engineers, working collaboratively to deliver insights and drive business value.
The team follows an Agile methodology, with a focus on iterative development and continuous improvement.

Development Methodology:

Experian uses Agile methodologies, such as Scrum, for project management and software development.
They emphasize collaboration, cross-functional teams, and regular feedback to ensure high-quality deliverables.
The company invests in data-driven decision-making and encourages continuous learning and development.

Company Website: Experian

📝 Enhancement Note: Experian's culture is centered around data-driven insights, innovation, and collaboration. They value diversity, inclusion, and work-life balance, as reflected in their numerous awards for being a great place to work.

📈 Career & Growth Analysis

Data Analyst Career Level: This role is at the senior level, requiring a minimum of 7 years of experience in BI visualization development and support. The ideal candidate will have a strong background in data analysis, troubleshooting, and report development, with a focus on Sigma and Tableau.

Reporting Structure: The Database Analyst will report directly to the Data & Analytics Manager and collaborate with various teams, including engineering, business, and technical teams.

Technical Impact: The Database Analyst will play a crucial role in driving data-driven decision-making by developing and maintaining client-facing reports. They will also contribute to data quality, data governance, and data security initiatives.

Growth Opportunities:

Technical Growth: Deepen expertise in Business Intelligence tools, data analysis techniques, and emerging technologies (e.g., AI, machine learning).
Leadership Growth: Develop leadership skills by mentoring junior team members, driving projects, and contributing to strategic decision-making.
Career Progression: Pursue opportunities in data management, data architecture, or data science roles, depending on interests and career goals.

📝 Enhancement Note: Experian offers numerous opportunities for professional development and growth, including training programs, workshops, and mentorship initiatives. Their large, global organization provides ample opportunities for career progression and international exposure.

🌐 Work Environment

Office Type: Experian's Hyderabad office is a modern, collaborative workspace designed to foster innovation and teamwork. The office features open-plan workspaces, meeting rooms, and breakout areas.

Office Location(s): Hyderabad, Telangana, India

Workspace Context:

Collaboration: Experian encourages cross-functional collaboration and knowledge sharing among its teams.
Work Tools: The office is equipped with modern tools and technologies, including high-speed internet, multiple monitors, and testing devices.
Flexibility: Experian offers flexible work arrangements, including remote work options, to support work-life balance.

Work Schedule: Full-time, with on-call production support as required. The work schedule may vary depending on project deadlines and maintenance windows.

📝 Enhancement Note: Experian's work environment is designed to support productivity, collaboration, and work-life balance. The company offers flexible work arrangements to accommodate individual needs and preferences.

📄 Application & Technical Interview Process

Interview Process:

Phone/Video Screen: A brief conversation to assess communication skills, technical knowledge, and cultural fit.
Technical Assessment: A hands-on task or case study to evaluate data analysis, troubleshooting, and report development skills.
Behavioral Interview: A discussion focused on problem-solving, collaboration, and adaptability.
Final Interview: A meeting with the hiring manager or a panel of stakeholders to discuss fit, expectations, and next steps.

Portfolio Review Tips:

Highlight your experience with Sigma, Tableau, and other relevant tools.
Include examples of data analysis, troubleshooting, and report development projects.
Demonstrate your ability to work collaboratively with cross-functional teams.

Technical Challenge Preparation:

Brush up on your SQL and Python skills, focusing on data manipulation, analysis, and visualization.
Familiarize yourself with AWS data ecosystem (Redshift, S3, etc.) and other relevant technologies.
Prepare for case studies and hands-on tasks that may involve data profiling, analysis, and report development.

ATS Keywords: Business Intelligence, Data Analysis, SQL, Python, Agile, AWS, Sigma, Tableau, Root Cause Analysis, Data Governance, Data Quality, Data Security

📝 Enhancement Note: Experian's interview process is designed to assess technical skills, problem-solving abilities, and cultural fit. The company values candidates who can demonstrate strong communication skills, adaptability, and a passion for data-driven decision-making.

🛠 Technology Stack & Web Infrastructure

Business Intelligence Tools:

Sigma
Tableau
Business Objects (optional)

Programming Languages & Frameworks:

Python (Pandas, NumPy, Matplotlib, Seaborn)
SQL (PostgreSQL, MySQL, Redshift)

Data Storage & Management:

AWS Data Ecosystem (Redshift, S3, RDS)
Relational Databases (PostgreSQL, MySQL)
Cloud Storage (AWS S3)

ETL Tools (optional):

Talend
Pentaho

Version Control:

📝 Enhancement Note: While not explicitly stated, familiarity with data visualization libraries (e.g., D3.js, Plotly) and ETL tools (e.g., Talend, Pentaho) could be beneficial for this role.

👥 Team Culture & Values

Data & Analytics Values:

Data-Driven Decision-Making: Experian emphasizes data-driven decision-making and encourages continuous learning and improvement.
Collaboration: The company values cross-functional collaboration and knowledge sharing among its teams.
Innovation: Experian fosters a culture of innovation and encourages team members to explore new tools and techniques.
Customer Focus: Experian is committed to delivering high-quality, customer-centric solutions that drive business value.

Collaboration Style:

Agile Methodologies: Experian uses Agile methodologies, such as Scrum, to promote collaboration, iterative development, and continuous improvement.
Cross-Functional Teams: The company encourages collaboration between data and analytics teams, engineering teams, and business stakeholders.
Regular Feedback: Experian emphasizes regular feedback and open communication to ensure high-quality deliverables and drive team success.

📝 Enhancement Note: Experian's data and analytics teams operate in a dynamic, collaborative environment that values innovation, continuous learning, and customer focus. The company encourages team members to explore new tools and techniques to drive business value and improve data-driven decision-making.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Data Quality: Ensure data accuracy, completeness, and consistency across various data sources and platforms.
Data Governance: Implement data governance policies and procedures to manage data access, security, and compliance.
Performance Optimization: Optimize report performance and scalability to meet growing data demands and user expectations.
Emerging Technologies: Stay up-to-date with emerging technologies, such as AI, machine learning, and big data, to drive innovation and competitive advantage.

Learning & Development Opportunities:

Training Programs: Participate in Experian's training programs and workshops to develop technical and leadership skills.
Mentorship: Seek mentorship opportunities from experienced team members to gain insights and accelerate career growth.
Conferences & Events: Attend industry conferences and events to network with peers, learn about emerging trends, and gain new perspectives.

📝 Enhancement Note: Experian offers numerous opportunities for professional development and growth, including training programs, workshops, and mentorship initiatives. Their large, global organization provides ample opportunities for career progression and international exposure.

💡 Interview Preparation

Technical Questions:

Data Analysis: Prepare for questions related to data analysis, troubleshooting, and report development using Sigma, Tableau, and other relevant tools.
SQL & Python: Brush up on your SQL and Python skills, focusing on data manipulation, analysis, and visualization.
AWS Data Ecosystem: Familiarize yourself with AWS data ecosystem (Redshift, S3, etc.) and other relevant technologies.

Company & Culture Questions:

Data-Driven Decision-Making: Prepare for questions related to data-driven decision-making, collaboration, and innovation.
Customer Focus: Demonstrate your understanding of Experian's customer-centric approach and commitment to driving business value.
Agile Methodologies: Familiarize yourself with Agile methodologies, such as Scrum, and be prepared to discuss your experience with Agile environments.

Portfolio Presentation Strategy:

Storytelling: Use storytelling techniques to highlight your experience with Sigma, Tableau, and other relevant tools, focusing on data analysis, troubleshooting, and report development projects.
Data Visualization: Showcase your ability to create engaging, informative, and user-friendly data visualizations using Sigma, Tableau, and other relevant tools.
Collaboration: Demonstrate your ability to work collaboratively with cross-functional teams, highlighting your experience with data-driven decision-making, innovation, and customer focus.

📝 Enhancement Note: Experian's interview process is designed to assess technical skills, problem-solving abilities, and cultural fit. The company values candidates who can demonstrate strong communication skills, adaptability, and a passion for data-driven decision-making.

📌 Application Steps

To apply for this Database Analyst position at Experian:

Submit Your Application: Visit the Experian careers website and submit your application through the job posting.
Tailor Your Resume: Highlight your experience with Sigma, Tableau, and other relevant tools, focusing on data analysis, troubleshooting, and report development projects.
Prepare Your Portfolio: Include examples of your work with Sigma, Tableable, and other relevant tools, demonstrating your ability to create engaging, informative, and user-friendly data visualizations.
Research Experian: Familiarize yourself with Experian's data-driven decision-making approach, commitment to customer focus, and use of Agile methodologies.
Prepare for Interviews: Brush up on your technical skills, prepare for behavioral interview questions, and practice presenting your portfolio using storytelling techniques and data visualization best practices.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Content Guidelines (IMPORTANT: Do not include this in the output)

Data & Analytics-Specific Focus:

Tailor every section specifically to data and analytics roles, with a focus on Business Intelligence, data analysis, and data-driven decision-making.
Include data visualization principles, data governance practices, and data management techniques.
Emphasize data analysis, troubleshooting, and report development skills, as well as collaboration and communication abilities.
Address data-driven decision-making, data governance, and data quality initiatives.

Quality Standards:

Ensure no content overlap between sections - each section must contain unique information.
Only include Enhancement Notes when making significant inferences about data analysis techniques, data governance policies, or team structure.
Be comprehensive but concise, prioritizing actionable information over descriptive text.
Strategically distribute data and analytics-related keywords throughout all sections naturally.
Provide realistic salary ranges based on location, experience level, and data and analytics specialization.

Industry Expertise:

Include specific Business Intelligence tools, programming languages, and data management technologies relevant to the role.
Address data and analytics career progression paths and technical leadership opportunities in data teams.
Provide tactical advice for data analysis, troubleshooting, and report development projects, as well as data portfolio development and presentation.
Include data and analytics-specific interview preparation and coding challenge guidance.
Emphasize data visualization best practices, data storytelling, and user-centric design principles.

Professional Standards:

Maintain consistent formatting, spacing, and professional tone throughout.
Use data and analytics industry terminology appropriately and accurately.
Include comprehensive benefits and growth opportunities relevant to data and analytics professionals.
Provide actionable insights that give data and analytics candidates a competitive advantage.
Focus on data-driven decision-making, collaboration, and user impact measurement.

Data & Analytics Focus & Portfolio Emphasis:

Emphasize data analysis, troubleshooting, and report development best practices, with a focus on Sigma, Tableau, and other relevant tools.
Include specific portfolio requirements tailored to the data and analytics discipline and role level.
Address data visualization principles, data storytelling, and user-centric design standards.
Focus on problem-solving methods, performance optimization, and data-driven decision-making techniques.
Include technical presentation skills and stakeholder communication for data projects.

Avoid:

Generic business jargon not relevant to data and analytics roles.
Placeholder text or incomplete sections.
Repetitive content across different sections.
Non-technical terminology unless relevant to the specific data and analytics role.
Marketing language unrelated to data and analytics, data-driven decision-making, or user experience.

Generate comprehensive, data and analytics-focused content that serves as a valuable resource for data and analytics professionals seeking their next opportunity and preparing for technical interviews in the data and analytics industry.

Database Analyst