Payment Ops Data Architect/Engineer Vice President

8 - 12 years

0 Lacs

Posted:6 days ago| Platform: Shine logo

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Work Mode

On-site

Job Type

Full Time

Job Description

You will be leveraging your technical skills to source and prepare data from a variety of data sources, such as traditional databases, no-SQL, Hadoop, and Cloud. Your role will involve working closely with data analytics staff within our team to understand requirements and collaborate on optimizing solutions while developing new ideas. Additionally, you will be collaborating with the Data Domain Architect lead on all aspects of Data Domain Architecture, including resource management. Furthermore, you will engage with Tech, Product, and CIB data partners to conduct research and implement use cases effectively. To be successful in this role, you should have a minimum of 8+ years of relevant work experience in roles such as software developer, data/ML engineer, data scientist, or business intelligence engineer. A Bachelor's degree in Computer Science/Financial Engineering, MIS, Mathematics, Statistics, or another quantitative subject is required. You should possess strong analytical thinking and problem-solving skills, along with the ability to grasp business requirements and effectively communicate complex information to diverse audiences. Collaboration across teams and at varying levels using a consultative approach is essential, as well as a general understanding of Agile Methodology. Moreover, you should have knowledge of cloud platforms and hands-on experience with tools like Databricks or Snowflake. Proficiency in traditional databases such as Oracle and SQL Server, as well as strong overall SQL skills and experience with Python/PySpark are necessary. Familiarity with ETL framework and tools, including Alteryx, is expected. A fundamental understanding of Data Architecture, the ability to profile, clean, and extract data from various sources, and experience in developing analytics and insights using tools like Tableau and Alteryx are important. Exposure to data science, AI/ML, and model development will be beneficial in this role.,

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