Overview
On Site
Accepts corp to corp applications
Contract - 6+ month(s)
Skills
Retail
SQL
ETL
Snowflake
validation procedures
Job Details
Description
In support of ongoing production reporting projects for the Retail Store Analytics team in
support of Global Retail Support, we require highly skilled Data Quality Engineers to ensure the
accuracy, consistency, and reliability of data across multiple reporting tools used by over
thousands of users worldwide.
The successful consultant will proactively identify and resolve data quality issues, support
user inquiries, and collaborate with our Product Manager, Analytics Engineers, Decision
Scientists and other Analysts and members of the team.
This is a hands-on role requiring strong SQL skills, analytical abilities, and excellent
communication skills.
In support of ongoing production reporting projects for the Retail Store Analytics team in
support of Global Retail Support, we require highly skilled Data Quality Engineers to ensure the
accuracy, consistency, and reliability of data across multiple reporting tools used by over
thousands of users worldwide.
The successful consultant will proactively identify and resolve data quality issues, support
user inquiries, and collaborate with our Product Manager, Analytics Engineers, Decision
Scientists and other Analysts and members of the team.
This is a hands-on role requiring strong SQL skills, analytical abilities, and excellent
communication skills.
Key Responsibilities
Develop and execute comprehensive testing and validation procedures for new and
enhanced metrics across our reporting tools. This includes identifying potential data quality
issues before they impact users.
Investigate and resolve data discrepancies and quality-related issues reported by users and
internal teams. This involves analyzing data, tracing logic through scripts and pipelines and
visual reporting tools and collaborating with our existing engineering teams to identify root
causes and implement solutions.
Manage and respond to data-related support tickets, escalating complex issues as needed.
Provide timely and accurate responses to users and internal stakeholders.
Effectively collaborate with the Product Manager and other technical roles to understand
data pipelines, metric definitions, and resolve data quality issues. Clearly communicate
technical information to both technical and non-technical audiences.
Develop and implement processes for identifying, analyzing, and resolving data exceptions.
Assist with access management issues related to our reporting tools and data assets.
Develop and execute comprehensive testing and validation procedures for new and
enhanced metrics across our reporting tools. This includes identifying potential data quality
issues before they impact users.
Investigate and resolve data discrepancies and quality-related issues reported by users and
internal teams. This involves analyzing data, tracing logic through scripts and pipelines and
visual reporting tools and collaborating with our existing engineering teams to identify root
causes and implement solutions.
Manage and respond to data-related support tickets, escalating complex issues as needed.
Provide timely and accurate responses to users and internal stakeholders.
Effectively collaborate with the Product Manager and other technical roles to understand
data pipelines, metric definitions, and resolve data quality issues. Clearly communicate
technical information to both technical and non-technical audiences.
Develop and implement processes for identifying, analyzing, and resolving data exceptions.
Assist with access management issues related to our reporting tools and data assets.
Key Qualifications
3+ years of experience as a Data Quality Engineer or similar role in a consulting capacity.
Strong SQL skills ability to write complex queries, analyze large datasets, and troubleshoot
data issues.
Experience working with large-scale data warehousing solutions (Snowflake preferred).
Experience with data pipelines and ETL processes (Airflow preferred).
Proficiency in Python (data manipulation and analysis).
Experience with data visualization tools (Tableau preferred).
Excellent problem-solving and analytical skills.
Excellent written and verbal communication skills.
Experience working with Git (GitHub preferred) and CI/CD pipelines.
Ability to understand and interpret complex data logic from scripts and pipelines.
Experience with data governance principles and best practices.
3+ years of experience as a Data Quality Engineer or similar role in a consulting capacity.
Strong SQL skills ability to write complex queries, analyze large datasets, and troubleshoot
data issues.
Experience working with large-scale data warehousing solutions (Snowflake preferred).
Experience with data pipelines and ETL processes (Airflow preferred).
Proficiency in Python (data manipulation and analysis).
Experience with data visualization tools (Tableau preferred).
Excellent problem-solving and analytical skills.
Excellent written and verbal communication skills.
Experience working with Git (GitHub preferred) and CI/CD pipelines.
Ability to understand and interpret complex data logic from scripts and pipelines.
Experience with data governance principles and best practices.
Additional Skills
Experience with custom BI tools and JavaScript front-end development.
Experience with data modeling and semantic layer design.
Familiarity with Agile development methodologies.
Experience with data profiling and data quality tools.
Experience with custom BI tools and JavaScript front-end development.
Experience with data modeling and semantic layer design.
Familiarity with Agile development methodologies.
Experience with data profiling and data quality tools.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.