976 KPMG India Jobs
Senior - Azure Data Engineering / ETL
KPMG India
posted 1mon ago
Flexible timing
Key skills for the job
Data Architecture Design: Designing and implementing scalable, distributed, and high-performance data architectures using AWS services like Amazon S3, Amazon Redshift, Amazon EMR, AWS Glue, and others.Data Processing and ETL: Building and managing Extract, Transform, Load (ETL) pipelines to collect, process, and transform large volumes of data using AWS tools like AWS Glue, Apache Spark, or custom scripts.Data Warehousing: Developing and managing data warehouse solutions using AWS Redshift or other relevant technologies to enable efficient data storage and analytics.Data Governance and Security: Implementing data governance frameworks, access controls, encryption, and compliance standards to ensure data security and regulatory compliance.Data Visualization and Analytics: Integrating data with analytics and visualization tools like AWS QuickSight, Tableau, or Power BI to derive insights and support decision-making processes.Performance Optimization: Optimizing data pipelines, storage, and querying performance for enhanced efficiency and cost-effectiveness.
Qualifications and Skills:AWS Expertise: Proficiency in various AWS data services like S3, Redshift, Glue, EMR, Lambda, Kinesis, and related AWS data analytics and storage solutions.Data Engineering Skills: Strong understanding of data modeling, ETL processes, data warehousing, data lakes, and big data technologies.Programming and Scripting: Proficiency in programming languages like Python, SQL, Scala, or Java, as well as scripting for data processing tasks.Data Visualization Tools: Familiarity with tools for data visualization and analytics like QuickSight, Tableau, or Power BI.Key Attributes:Analytical Thinking: Ability to analyze complex data sets, identify patterns, and derive actionable insights.Problem-Solving Skills: Capability to troubleshoot data-related issues and optimize data pipelines for efficiency.Team Collaboration: Effective communication and collaboration with cross-functional teams, data scientists, analysts, and stakeholders.
Employment Type: Full Time, Permanent
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