Finding the best job has never been easier
Nike Senior Data Quality United States, Oregon, Beaverton 943541798
Share
SENIOR, DATA QUALITY
GRADE 35
As a Data Quality Analystin Product Data Governance, you will primarily focus on our Data Quality program.
REQUIRED SKILLS:
•Minimum of Bachelors degree in Computer Science, Data Analytics or related field or equivalent combination of education, experience or training.
Data Analysis:Proficient in analyzing large datasets to identify trends, patterns, inconsistencies, and potential data quality issues.
Technical Expertise:Strong skills in SQL and Alteryx for data manipulation, transformation, and automation of data quality checks. Familiarity with Python for automation and scripting (optional).
Data Profiling:Ability to perform data profiling to assess the quality of data sources and identify areas needing improvement.
Data Cleansing:Expertise in data cleansing techniques to correct or remove inaccuracies, inconsistencies, and errors in data sets.
Reporting:Capable of creating detailed reports and dashboards that highlight data quality metrics and trends, using tools like Tableau or Power BI
Root Cause Analysis:Skilled in performing root cause analysis to determine the origins of data quality issues and propose effective solutions.
Data Management Principles:Familiarity with data governance, data stewardship, and the role these play in maintaining data quality.
Tool Proficiency: Competence in using data quality tools and platforms like Talend, Alteryx, Informatica, or similar software to automate and streamline data quality processes. Familiarity with cloud-based data platforms (Snowflake, Databricks) and their role in enterprise data quality.
ETL Processes:Familiarity with ETL (Extract, Transform, Load) processes and how they relate to maintaining data quality during data movement and transformation.
Data Validation Techniques:Understanding of various data validation techniques to ensure the accuracy and integrity of data.
Detail-Oriented: Pays close attention to details, ensuring that even small data issues are identified and addressed.
Proactive: Actively seeks out potential data quality issues and works to resolve them before they become larger problems.
Curiosity: Shows a strong desire to understand data at a deeper level, always looking for ways to improve quality.
Problem-Solving: Demonstrates strong problem-solving skills, especially when facing complex data quality issues.
Adaptability: Adapts quickly to new tools, technologies, and processes to improve data quality.
KEY JOB ACCOUNTABILITIES
Data Quality Assessment and Monitoring:Perform ongoing assessments of data quality across various databases/systems and track key data quality metrics, such as accuracy, completeness, consistency, and timeliness, and report on these metrics regularly.
Data Profiling: Analyze data sets to understand their structure, relationships, and quality, identifying any issues such as duplicates, missing values, or outliers.
Data Cleansing and Enrichment:Develop/implement processes for cleansing data, including removing duplicates, correcting errors, and filling in missing information.
Data Quality Standards and Procedures:Establish and maintain data quality standards and guidelines that align with organizational goals and industry best practices; create and implement procedures for data entry, validation, and maintenance to ensure high-quality data.
Reporting and Documentation:Create and maintain reports and dashboards that provide insights into the current state of data quality; highlight trends over time.
These jobs might be a good fit
