Software Development Engineer
| Location | Bengaluru |
|---|---|
| Experience | Minimum 2 year(s) |
| Job Type | Full-time |
Job Description
Project Role: Software Development Engineer
Project Role Description: Analyze, design, code and test multiple components of application code across one or more clients. Perform maintenance, enhancements, and/or development work.
Must Have Skills
- Microsoft Power BI
Good to Have Skills
- Power BI
Experience
Minimum 2 year(s) of experience is required
Educational Qualification
15 years full-time education
Summary
As a Software Development Engineer, you will analyze, design, code, and test multiple components of application code across one or more clients. You will perform maintenance, enhancements, and/or development work. Your typical day will involve analyzing requirements, designing software solutions, writing code, and conducting testing to ensure the quality of the application. You will collaborate with cross-functional teams and contribute to the overall success of the project.
Roles and Responsibilities
- Expected to perform independently and become an SME.
- Required active participation/contribution in team discussions.
- Contribute in providing solutions to work-related problems.
- Collaborate with cross-functional teams to gather requirements and understand business needs.
- Design and develop software solutions based on client requirements.
- Write clean, efficient, and maintainable code.
- Conduct unit testing and debugging to ensure the quality of the application.
- Participate in code reviews and provide constructive feedback.
- Stay updated with the latest industry trends and technologies.
- Assist in troubleshooting and resolving software defects and issues.
Professional and Technical Skills
- Proficiency in Microsoft Power BI.
- Strong understanding of statistical analysis and data visualization.
- Experience with data visualization tools such as Tableau or Power BI.
- Hands-on experience in implementing various data engineering techniques.
- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity.
