Data Analyst

Cognizant; Hyderabad; On-site; INR 900,000 - 1,200,000; Full time

Job summary

Cognizant is seeking a Senior Data Analyst in Hyderabad to lead analytical projects, leveraging advanced SQL skills to interpret complex datasets and develop dashboards. This role requires collaboration with business teams to drive insights and assist in strategic decision-making.

The ideal candidate will have over 5 years of experience, a degree in a quantitative discipline, and proficiency with data visualization tools. Excellent communication skills are essential to convey insights effectively.

Qualifications

• 5+ years of experience in data analysis or business intelligence.
• Expert-level proficiency in SQL with complex querying capabilities.
• Strong understanding of data architecture and ETL/ELT principles.

Responsibilities

• Utilize SQL skills to analyze and manipulate complex datasets.
• Develop scalable dashboards and reports for KPI monitoring.
• Collaborate with product managers to answer business questions.

Skills

Advanced SQL skills

Data visualization tools (Tableau, Looker, Power BI)

Statistical analysis

Python or R

Communication and interpersonal skills

Education

Bachelor's degree in a quantitative field

Tools

Google BigQuery

GitHub

Job description

Job Description

Senior Data Analyst

Location: Hyderabad, IN – Work from Office

Role & responsibilities

Advanced Data Analysis: Utilize advanced SQL skills to query, analyze, and manipulate large, complex datasets. Develop and maintain robust, scalable dashboards and reports to monitor key performance indicators (KPIs).

• Source Code management: Proven ability to effectively manage, version, and collaborate on code using codebase management systems like GitHub. Responsible for upholding data integrity, producing reproducible analyses, and fostering a collaborative database management environment through best practices in version control and code documentation.
• Strategic Insights: Partner with product managers and business stakeholders to define and answer critical business questions. Conduct deep-dive analyses to identify trends, opportunities, and root causes of performance changes.
• Data Architecture & Management: Work closely with data engineers to design, maintain, and optimize data schemas and pipelines. Provide guidance on data modeling best practices and ensure data integrity and quality.
• Reporting & Communication: Translate complex data findings into clear, concise, and compelling narratives for both technical and non-technical audiences. Present insights and recommendations to senior leadership to influence strategic decision-making.
• Project Leadership: Lead analytical projects from end to end, including defining project scope, methodology, and deliverables. Mentor junior analysts, fostering a culture of curiosity and data-driven problem-solving.

Required Skills & Experience

• Bachelor's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, or a related discipline.
• 5+ years of professional experience in a data analysis or business intelligence role.
• Expert-level proficiency in SQL with a proven ability to write complex queries, perform window functions, and optimize queries for performance on massive datasets.
• Strong understanding of data architecture, including data warehousing, data modeling (e.g., star/snowflake schemas), and ETL/ELT principles.
• Excellent communication and interpersonal skills, with a track record of successfully influencing stakeholders.
• Experience with a business intelligence tool such as Tableau, Looker, or Power BI to create dashboards and visualizations.
• Experience with internal Google/Alphabet data tools and infrastructure, such as BigQuery, Dremel, or Google-internal data portals.
• Experience with statistical analysis, A/B testing, and experimental design.
• Familiarity with machine learning concepts and their application in a business context.
• A strong sense of curiosity and a passion for finding and communicating insights from data.
• Proficiency with scripting languages for data analysis (e.g., App scripting, Python or R) would be an added advantage.