Equifax - Data Quality Analyst - SQL/Tableau

Data Quality Analyst Consumer.

The Chief Data Office is a fast growing team critical to the Bureaus objectives of transforming into a Data and Analytics organization.

It plays a critical function in building and supporting best-in-class data assets.

Data is our second most important asset after our people.

As such, Data Quality is a key component of our overall business strategy, key differentiator, and critical to revenue generation.

The role will be based in India-Pune.

Synopsis of the role :

The Data Quality analyst is a high performing role that supports the management of data in the Canadian Data Library.

This individual will work within a network of product owners, data scientists, data stewards, technologists and other data management professionals to ensure our second most important asset is of the best quality and fit for use.

The Data Quality analyst should be tenacious, creative, curious, with an appetite for growth and innovative business leadership.

As a Data and Analytics company, this role is critical to revenue generation and key to growth.

They are responsible for the investigation, correction and prevention of data issues.

What Youll Do :

- Data Quality : Work with the data steward and the data modernization team to continuously ensure that the highest possible levels of data quality is ensured.

- Quality Monitoring : Develop, support and monitor automated threshold based dashboards and reports that efficiently and reliably identify areas for further investigation and improvement.

- Work with the data steward to support the resolution of the findings in a timely manner.

- Data Quality Investigations : Analyze and evaluate data quality issues, clarifying issues and recommending corrective action.

- Continuous improvement : work with an evergreen roadmap of initiatives, data management, product and IT to identify, define, and implement data quality processes and requirements.

- Analyze data and provide data quality assurance for support teams.

- Maintain documentation and share knowledge base.

- Assist in development and implementation of new processes, procedures and tools to analyze data and insights.

What will you need?.

- Bachelors or advanced degree in a quantitative discipline such as Computer Science, Engineering, Economics, Mathematics, Statistics, or Physics (essential) or Business with combination of work experience.

- 2+ years experience with data and business insights analysis which identify and drive ongoing excellence in data quality practices.

- 2+ years experience in credit risk, financial services, marketing, fraud, insurance, or equivalent industry.

- Intermediate to advanced knowledge of data analysis methods and the ability to analyze and resolve complex data related issues (SQL, Google Big Query, Python, Hadoop, etc.

- Experience with business and/or technical documentation and the assessment of existing processes and systems.

- Experience with business intelligence tools such as Tableau, Looker.

- Solid experience in delivering projects with data components (e.

- Worked in data governance, warehousing, or analytics environment).

- Excellent communication skills, verbal and written.

- Able to work independently with general supervision/oversight to achieve short-term (weekly/monthly) performance expectations.

- Adaptability and ability to deal with ambiguity.

What could set you apart?.

- Experience in designing and building analytics solutions to solve real world business problems.

- Creativity, drive and the ability to identify efficiencies and opportunities.

- The ability to collaborate with multiple teams and get teams to work together.

- Agile project management skills, including experience with Jira.

- The demonstrated ability to make Data Quality a function that enables business to function more efficiently and with greater results.

- Expertise in the financial services industry.

- The ability to manage multiple high-impact projects at the same time.

- Experience with solving analytical and business problems using generative AI.