Job Description :-
| Company: | KPMG |
| Job Role: | Executive – Software Engineering |
| Batches: | 2021-2025 |
| Degree: | Bachelor’s Degree |
| Experience: | Freshers/Experienced |
| Location: | Pune, India |
| CTC/Salary: | INR 5.5-14 LPA (Expected) |
Responsibilities
Functional Skills
- Determining, creating, and implementing internal process improvements, such as redesigning infrastructure for increased scalability, improving data delivery, and automating manual procedures.
- Building analytical tools that make use of the data flow and offer a practical understanding of crucial company performance indicators like operational effectiveness and customer acquisition.
- Helping stakeholders, including the data, design, product, and executive teams, with technical data difficulties.
- Working on data-related technical challenges while collaborating with stakeholders, including the Executive, Product, Data, and Design teams, to support their data infrastructure needs.
- Remaining up-to-date with developments in technology and industry norms can help you to produce higher-quality results.
Technical Skills:
- Analyze large datasets to derive actionable insights and support decision-making processes.
- Develop and maintain data pipelines using PySpark and other data processing tools.
- Write efficient SQL queries to extract, transform, and load data from various sources.
- Implement data models and schemas to organize and optimize data storage and retrieval.
- Perform data normalization and denormalization to ensure data integrity and accessibility.
- Collaborate with data engineers to centralize and manage data assets.
- Ensure data quality through validation and cleansing processes.
- Utilize CI/CD pipelines to streamline data deployment and maintain continuous integration.
Qualifications:
- Proven experience in data analytics and working with large datasets.
- Proficiency in Python, including libraries such as Pandas and Numpy for data manipulation.
- Strong SQL skills for querying and managing databases.
- Experience with PySpark for large-scale data processing.
- Basic understanding of Hadoop and its ecosystem.
- Familiarity with data engineering concepts and best practices.
- Knowledge of data modeling, including schemas, normalization, and denormalization techniques.
- Understanding of data centralization, cardinality, and data quality principles.
- Good to have experience in CI/CD pipelines and tools.
Banking
- Deep understanding of banking operations, financial products, and regulatory frameworks
- Experience with data modeling, ETL processes, and statistical analysis
- Prior experience in retail or corporate banking analytics
- Analyze banking data including customer transactions, loan performance, and financial statements
- Support credit risk analysis and fraud detection initiatives
- Maintain and optimize banking databases and data pipelines.
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