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 operationsProficient in SQL, ETL and various data analysis toolsWell-versed in Charles River IMS (CRD)and its functionalitiesExcellent analytical and problem-solving skillsExperienced in quality assurance life cycles and testing methodologiesEffective communicator, capable of engaging with both technical and non-technical stakeholdersDetail-oriented, skilled in identifying and correcting data discrepancies and errorsStrong analytical skills for examining data and recognizing patterns or issuesFamiliarity with Agile methodology and Atlassian tools is advantageousTechnically proficient with data management tools and software, such as SQL, Excel, and data visualization toolsKnowledge in snowflakeProblem-solving skills to devise solutions for enhancing data qualityExcellent verbal and written communication abilities for collaborating with team members and stakeholdersSelf-motivated and proactive in identifying and resolving data quality issuesStrong organizational skills and attention to detailAbility to work independently and as part of a teamEager to learn and adapt to new technologies and methodologies