Data Analyst

KPMG Assurance and Consulting Services LLP; New Delhi; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

KPMG Assurance and Consulting Services LLP in Delhi seeks a senior data analytics professional with 6-10 years of experience to design and deliver enterprise analytics, BI, and data engineering solutions. The role covers Hadoop ecosystem, ETL, data warehousing, and stakeholder engagement.

You will work in Agile environments, develop dashboards, ensure data quality, and optimize performance across large-scale datasets for BFSI and related sectors.

Qualifications

• 6-10 years of experience in data analytics, BI, data engineering, or big data environments.
• Hands-on experience with Hadoop clusters and ecosystem tools such as Hive, Spark, HBase, Sqoop, Impala, and Kafka.
• Strong SQL development, query optimization, and database performance tuning.
• Experience handling large-scale datasets ranging from millions to billions of records.
• Experience designing and managing ETL processes and data warehousing solutions.
• Working knowledge of Agile project delivery methodologies.
• Experience in BFSI/Telecom/Retail or similar domains preferred.

Responsibilities

• Design, develop, and maintain enterprise-scale analytics and reporting solutions.
• Analyze large and complex datasets to generate actionable business insights.
• Develop dashboards, reports, KPIs, and performance monitoring frameworks.
• Translate business requirements into scalable analytical solutions.
• Manage and support Hadoop ecosystem components including HDFS, Hive, HBase, Sqoop, Spark, Impala.
• Develop and optimize big data processing workflows for structured and unstructured datasets.
• Ensure data quality, integrity, security, and governance across platforms.
• Monitor cluster performance and recommend optimization strategies.
• Design, build, and maintain ETL/ELT pipelines for large-scale data processing.
• Integrate data from multiple sources; support data warehousing initiatives.
• Troubleshoot and resolve data processing and performance issues.
• Develop complex SQL queries, stored procedures, and data transformations.
• Optimize query performance and database workloads.
• Prepare technical documentation and knowledge transfer artifacts.
• Collaborate with business users and stakeholders to gather requirements.
• Present analytical findings and recommendations to project stakeholders.
• Support project planning, estimation, and delivery activities.
• Contribute to proposal development and client presentations.

Skills

SQL & Advanced SQL

Hadoop Ecosystem

Apache Spark

Hive / HBase

ETL Development

Data Warehousing

Data Modeling

BI & Reporting

Performance Optimization

Data Quality Management

Education

Bachelor's Degree in CS/IT/Engineering/DS

Master's Degree (MBA/MCA/M.Tech/MS Analytics) preferred

Tools

Power BI

Tableau

Qlik

Azure Data Lake

Azure Synapse

AWS Big Data Services

Databricks

Kafka

Snowflake

Airflow

Job description

Key Responsibilities

Data Analytics & Business Intelligence

• Design, develop, and maintain enterprise-scale analytics and reporting solutions.
• Analyze large and complex datasets to generate actionable business insights.
• Develop dashboards, reports, KPIs, and performance monitoring frameworks.
• Translate business requirements into scalable analytical solutions.

Big Data Management

• Manage and support Hadoop ecosystem components including HDFS, Hive, HBase, Sqoop, Spark, Impala, and related technologies.
• Develop and optimize big data processing workflows for structured and unstructured datasets.
• Ensure data quality, integrity, security, and governance across platforms.
• Monitor cluster performance and recommend optimization strategies.

Data Engineering & ETL

• Design, build, and maintain ETL/ELT pipelines for large-scale data processing.
• Integrate data from multiple internal and external sources.
• Support data warehousing initiatives and enterprise data models.
• Troubleshoot and resolve data processing and performance issues.

Database Development & Optimization

• Develop complex SQL queries, stored procedures, and data transformation scripts.
• Optimize query performance and database workloads.
• Conduct data validation, reconciliation, and quality assessments.
• Support performance tuning activities across data platforms.

Stakeholder Management

• Collaborate with business users, functional teams, and technology stakeholders to gather requirements.
• Present analytical findings and recommendations to project stakeholders.
• Support project planning, estimation, and delivery activities.
• Contribute to proposal development, solutioning, and client presentations where required.

Project Delivery

• Work within Agile/Scrum delivery frameworks.
• Participate in sprint planning, backlog grooming, and release management activities.
• Ensure timely delivery of project milestones while maintaining quality standards.
• Prepare technical documentation, data dictionaries, and knowledge transfer artifacts.

Required Experience

• 6-10 years of experience in Data Analytics, Business Intelligence, Data Engineering, or Big Data environments.
• Hands‑on experience with Hadoop clusters and ecosystem tools such as Hive, Spark, HBase, Sqoop, Impala, and Kafka.
• Strong expertise in SQL development, query optimization, and database performance tuning.
• Experience handling large-scale datasets ranging from millions to billions of records.
• Proven experience in designing and managing ETL processes and data warehousing solutions.
• Working knowledge of Agile project delivery methodologies.
• Experience in Banking, Financial Services, Insurance (BFSI), Telecom, Retail, Government, Healthcare, or similar domains will be preferred.

Technical Skills

Essential Skills

• SQL, Advanced SQL Programming
• Hadoop Ecosystem
• Apache Spark
• Hive / HBase
• ETL Development
• Data Warehousing
• Data Modeling
• Business Intelligence & Reporting
• Performance Optimization
• Data Quality Management

Preferred Skills

• Python / PySpark
• Power BI / Tableau / Qlik
• Azure Data Lake / Azure Synapse
• AWS Big Data Services
• Databricks
• Kafka
• Snowflake
• Airflow
• Machine Learning Fundamentals

Educational Qualifications

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science, Statistics, Mathematics, or a related discipline from a recognized university.
• Master's Degree (MBA, MCA, M.Tech, MSc Analytics/Data Science, or equivalent) will be an added advantage.