Data Quality Specialist

The Data Quality Specialist will provide Data Quality oversight in the form of data error detection, correction and prevention. The Data Quality Analyst will monitor data collected, stored, transformed and/or used from a variety of systems and sources (external and internal) in order to ensure that it conforms to a set of defined minimum acceptable standards and satisfies regulatory requirements.

This role will work closely with the Data Governance team and the Data Stewards to accelerate the rollout of the Data Governance program through identifying Data Quality issues, resolving DQ gaps/issues and recommending effective data controls in order to avoid recurrence of identified Data Quality issues.

The Data Quality Analyst will also be a key resource to the delivery of a Data Quality project as well as the Data Remediation program.

Duties:

• Profile critical business data (CDEs) against a set of defined data quality dimensions, standards and rules in order to produce a view of the Data Quality status
• Design & Implement data error detection models
• Produce periodic dashboards/visualisations to report on the Data Quality status
• Conduct root cause analysis on identified data quality issues and recommend data quality controls to resolve gaps/issues
• Partner with Data Stewards to Investigate, troubleshoot and document data issues from internal and external data sources
• Provide recommendations for resolving identified data quality issues via data integration, business process improvement, system improvements, user training and automated approaches
• Periodically communicate insights on the materiality of identified data quality issues and their potential impact/s
• Work closely with development teams to improve system design/s to enforce best practice data creation & maintenance processes
• Analyse data for conformance to design specification (source-to-target) & expected/anticipated behaviours
• Analyse data for compliance to defined policies (data retention, data privacy, data destruction etc) and regulatory requirements (highlight the impact of poor-quality data, from a regulatory, compliance, finance and reputation perspective)
• Establish, monitor, and report on Service Level Agreements of external data assets with the outsourcing vendor as it relates to defined data quality standards and production performance.
• Work with technical and operational subject matter experts to understand and collect metadata about systems, processes, reports, controls, data movement, and business terminology
• Contribute to agile story refinement/defining requirements for the Data Quality roadmap
• Participate in estimating work necessary to realize an agile story/requirement through the delivery lifecycle
• Identify gaps in adherence to data management standards and work with appropriate partners to develop plans to close gaps.
• Partner with business area data stewards to maintain a list of identified business rules and data quality rules.
• Provide analytic and project management support to data quality initiatives

Experience:

• Attention to Detail: Data is precise. Vigilant in analysis to come to correct conclusions
• Strong understanding of the Data Management Body of Knowledge (DAMA- DMBOK)
• +5 years’ experience data quality management and data governance
• Analytical Skills: Work with large amounts of data: facts, figures, and number crunching
• Knowledge of statistics and experience using statistical packages for analysing datasets
• Strong analytical skills with the ability to collect, organize, analyse, and disseminate significant amounts of information with attention to detail and accuracy
• Adept at queries, report writing and presenting findings
• Ability to produce dashboards to drive remediation
• Ability to work in an agile methodology
• Communication Skills: Present findings or translate the data into an understandable document. Write and speak clearly, easily communicating complex ideas
• Critical Thinking: Must look at the numbers, trends, and data and come to new conclusions based on the findings.
• Ability to produce solutions using:
  • Microsoft Excel (Power Pivot, Power Query)
  • Microsoft SQL Integration Services
  • Microsoft SQL Analysis Services
  • Microsoft SQL Reporting Services
  • Microsoft Data Quality Services (or any data quality tool)
  • Microsoft PowerBI
  • MS Office, MS Visio
  • Knowledge of & Scaled Agile Framework (SAFe) practices will be advantageous
  • Knowledge of Cloud services (Azure & AWS), Power BI, ETL, JIRA

Qualifications/ Certification:

• B Sc Computer Science / Informatics,
• Certified Data Management Professional (CDMP) – advantageous