Data Quality Analyst

Our TOP CLIENT has retained us for a Data Quality Analyst role. They are known and highly recognized for their stability and commitment to a collaborative teamwork environment. The Data Quality Analyst will be responsible acquiring data from primary or secondary sources. This position involves obtaining legacy data from the former billing system, and mapping it to fit the billing system data model.



Location: Remote

Salary: $80K to $90K



Must Have skills:

Strong SQL skills

Python scripting

Database tools like pgAdmin, Toad, or DataGrip

Relational Databases experience (any)



Data collection: Acquiring data from primary or secondary sources.This position involves obtaining legacy data from the former billing system, and mapping it to fit our billing system data model. We sometimes do this ETL work internally, and/or work with ETL partners. Analytical skills are important tool, and just being comfortable working with data files.

• Data interpretation: Using statistical techniques to analyze data and draw logical conclusions.
• Data visualization: Using tools to identify patterns and present findings to stakeholders.
• Report and presentation development: Creating reports and presentations to explain data to stakeholders, IT representatives, and other data analysts.
• Data quality control: Validating and linking data, and providing quality assurance for imported data.
• Data protection: Understanding data protection issues and processing confidential data according to guidelines.
• Confirms project requirements by studying client requirements: collaborating with others on development and project teams.
• Works closely with project managers to understand and maintain focus on their analytics needs, including critical metrics and KPIs, and deliver actionable insights to relevant decision-makers
• Proactively analyze data to answer key questions for stakeholders or yourself, with an eye on what drives business performance, and investigate and communicate which areas need improvement in efficiency and productivity
• Create and maintain rich interactive visualizations through data interpretation and analysis, with reporting components from multiple data sources
• Gather, interpret, and present data to help others understand and solve problems.
• Turn project requirements into custom-formatted reports, and ability to analyze business procedures and recommend specific types of data that can be used to improve upon them.
• Develop, implement, and maintain leading-edge analytics systems, taking complicated problems and building simple frameworks.