Tdm Developer

Description:

As a TDM Developer, your primary responsibility will be to leverage your expertise in Pyspark and Python to create and transform test data. You will work closely with cross-functional teams, including data engineers, software developers, and quality assurance professionals, to ensure the accuracy and effectiveness of our test data. This role requires a strong understanding of data manipulation, the ability to work with large datasets, and a keen eye for details.

• Utilize Pyspark and Python to develop and maintain efficient data pipelines for creating test data.
• Apply your knowledge of data manipulation techniques to transform raw data into relevant and representative test datasets.
• Collaborate with data engineers and software developers to understand data requirements and ensure the availability of appropriate test data.
• Perform data profiling and analysis to identify data quality issues and make recommendations for improvement.
• Assist in the development of data validation strategies and quality assurance processes.
• Collaborate with the quality assurance team to ensure that test data meets the required criteria.
• Keep abreast of industry best practices and emerging technologies related to data management and test data creation.
• Work closely with stakeholders to understand their needs and provide data-driven solutions.
• Document processes, procedures, and best practices related to test data creation and management.

Let’s talk about the team:

Capgemini Financial Services is a Global Strategic Business Unit that provides information technology and consultancy services to the Banking, Capital Markets and Insurance industries. Capgemini FS brings you leading insights & deep industry experience to drive the future of Financial Services. Our customers count on us for the very latest in innovative service offerings & next generation global delivery.

Let’s talk about your capability and experience:

• Proficiency in PySpark and Python for data manipulation and transformation.
• Expert in SQL with basic knowledge of Databricks and its capabilities for data processing and analysis.
• Familiarity with data profiling techniques and data quality assessment.
• Experience working with large datasets and data validation.
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills to work effectively with cross-functional teams.
• Basic understanding of software development and quality assurance processes is a plus.