Data Quality Analysts

Overview

We are seeking a highly skilled Data Quality Analyst with 3 to 6 years of experience and a strong foundation in both business and technical expertise in Investment Banking Domain. The ideal candidate will be an analytical thinker, adept at problem-solving, reviewing data quality checks, and proposing new ones. As a Data Quality Analyst, you will ensure the accuracy, consistency, and reliability of data within the organization.

Key Responsibilities

• Perform comprehensive data quality checks and propose enhancements to existing processes
• Analyze and solve complex problems related to data quality in the Investment Banking domain
• Collaborate with cross-functional teams to ensure data integrity across various systems
• Support Business System Analysis ,Project Management, and Quality Assurance initiatives
• Work on Trade Life Cycle and Management modules, including Front, Middle, and Back- office operations
• Utilize tools such as Charles River Investment Management System (CRD), SQL for data analysis
• Engage in extended testing areas, including End to End Performance Testing
• Conduct Data Validation and Cleansing to identify and rectify errors and inconsistencies, ensuring high data quality
• Continuously monitor data quality metrics and trends to pinpoint areas needing improvement
• Perform Data Quality Assessments and audits to evaluate data quality
• Collaborate closely with data engineers, data scientists, and other stakeholders to uphold data quality standards
• Maintain detailed documentation of data quality processes and standards
• Create and present reports on data quality metrics and improvements to management

Required Skills

• Strong expertise in investment banking, capital markets -

  Front, Middle and Back office operations

• Proficient in SQL, ETL and various data analysis tools
• Well-versed in Charles River IMS (CRD)and its functionalities
• Excellent analytical and problem-solving skills
• Experienced in quality assurance life cycles and testing methodologies
• Effective communicator, capable of engaging with both technical and non-technical stakeholders
• Detail-oriented, skilled in identifying and correcting data discrepancies and errors
• Strong analytical skills for examining data and recognizing patterns or issues
• Familiarity with Agile methodology and Atlassian tools is advantageous
• Technically proficient with data management tools and software, such as SQL, Excel, and data visualization tools
• Knowledge in snowflake
• Problem-solving skills to devise solutions for enhancing data quality
• Excellent verbal and written communication abilities for collaborating with team members and stakeholders
• Self-motivated and proactive in identifying and resolving data quality issues
• Strong organizational skills and attention to detail
• Ability to work independently and as part of a team
• Eager to learn and adapt to new technologies and methodologies