What are the responsibilities and job description for the Data Quality Analyst position at Source Code Technologies LLC?
We are seeking a highly skilled Data Quality Analyst with 6 to 10 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