Data Quality Lead

JMMB - Data Quality Lead

Company: Jamaica Money Market Broker Limited

Industry: Financial Services

Location: New Kingston, St. Andrew, Jamaica

Department: Information Systems Department

Job Type: Full-time (Remote)

Benefits: Health, Pension, Paid Vacation, Uniform, ESOP, Motor Vehicle Allowance

SUMMARY:

Reporting directly to the Group Management Information Systems (MIS) Manager, the Data Quality Lead will define standards and management of first-class data quality and will work to embed best practice within the organisation. Inspect processes and data, set data quality objectives and also check the efficiency and functionality of these processes. Set testing and quality standards. The Data Quality Lead will manage and train data quality analyst in how to examine data and turn it into information and insight that will assist the organization in business decisions. They will work very closely with all facets of the organisation including the security unit and IT infrastructure to enhance and ensure good data management, in line with appropriate regulative requirements.

MAIN DUTIES & RESPONSIBILITIES:

• Monitor performance and quality control plans to identify any issues or ways to improve systems and database designs.
• Work with the Analysis Team to build, deploy and administer self-service analytics across business units.
• Work with Analytics Team to deliver on key analytics projects. This will include data provisioning, exploratory data analysis, data visualization and in some instances, machine learning and statistical modeling.
• Work with business stakeholders to define and then execute the data management governance model, including data ownership and data quality standards.
• Utilize the existing diverse analytics tools to turn data into actionable insights with the goal of creating a data-driven culture across the organization.
• Data analysis and interpretation to identify quality trends in source and processed data.
• Resolve data quality problems, and collaborate with database developers, and data engineering analysts to improve systems and database designs.
• Ensure delivery of authoritative, accurate, timely, consistent and complete data as required by the organization
• Manage all Enterprise data quality issues, including but not limited to, documentation, analysis, implementation and testing.
• Management of data quality dashboards.
• Consult with project teams to ensure good data quality practices are incorporated into the lifecycle.
• Provide recommendations and best practices for data element, data definitions, business rule writing, and metadata management procedure.
• Lead the Enterprise Data Management/Data Quality team including contractors, where applicable.
• Research technologies that will assist with the improvement of data quality.

EDUCATION, TRAINING & WORK EXPERIENCE REQUIRED:

• Master's degree in Computer science, or Information Technology or equivalent qualification from a recognized tertiary institution.
• Six (6+) years' experience in data quality analysis, business intelligence and reporting, and software design principles.
• Proficiency in statistical techniques.
• Proficiency in using enterprise analytics platforms, data visualization tools.
• Expertise in standard databases, query tools, and programming languages such as SQL, and Extract, Transform and Load (ETL) tools.
• Working proficiency in Microsoft SQL Server Integration Services (SSIS).
• Training or experience in data warehousing tools and concepts, business intelligence (BI) and business performance analytics and reporting.
• Experience managing projects and teams of two (2+) people.
• Excellent problem-solving skills for data management and continuous process improvement.
• Knowledge of data quality, data management, and master data management concepts.
• Strong analytical, problem solving and organizational skills.
• Strong oral and written communication skills.
• Working knowledge of financial sector instruments, laws, regulations, ethics and terminology, a plus.
• Good understanding of technical data forensics.

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