Data Quality Analyst

As a Data Quality Analyst, you will be responsible for ensuring the accuracy, integrity, and reliability of our data across multiple systems and sources. You will collaborate closely with data engineers, analysts, and business teams to identify, analyze, and resolve data quality issues. Your work will directly support business operations and decision-making by maintaining high standards of data quality.

Key Responsibilities:

• Data Validation: Verify data accuracy, completeness, and consistency across various sources and systems. Identify and resolve discrepancies and errors.
• Data Quality Assurance: Conduct rigorous quality checks on incoming and existing data to ensure it meets business and compliance requirements.
• Data Integrity: Ensure the integrity of data throughout its lifecycle, from ingestion to storage and reporting.
• Issue Identification & Resolution: Detect and troubleshoot data quality issues by conducting root cause analyses and working with cross-functional teams to implement solutions.
• Collaboration: Work with business, engineering, and data teams to continuously improve data quality and governance standards.
• Documentation: Maintain thorough documentation of data quality processes, issues, resolutions, and improvements.
• Reporting & Monitoring: Develop and manage data quality dashboards and reports to provide visibility into data quality metrics.
• Data Governance: Contribute to the development and enforcement of data governance policies and standards across the organization.

Qualifications:

• Bachelor's degree.
• Strong attention to detail and accuracy in handling data.
• Familiarity with SQL and data profiling for data validation and analysis.
• Excellent problem-solving and analytical skills.
• Strong collaboration and communication abilities.
• Ability to work independently and manage deadlines.
• Understanding of data management principles, including data quality, governance, and integrity.
• Experience working with data quality tools and technologies or Snowflake is a plus

Sample Scenario/Review for Data Validation:

Review the following scenario and describe the steps you would take to ensure data quality:

You are tasked with reviewing a set of customer order data for discrepancies and inconsistencies.

ORDER TABLE:

Order_ID, Customer_ID, Order_Date, Product_Code, Quantity, Address

2001, C001, 15/09/23, P001, 10, "123 Elm St, NY"

2002, C002, 18/09/23, P002, 5, 456 Maple Ave

2003, C003, 20/09/23, P003, NULL, "789 Oak Dr, CA"

2004, C001, "September 19, 2023", P001, 10, "123 Elm St, NY"

2001, C004, 21/09/23, P004, 7, NULL

2006, C005, N/A, P005, 2, "789 Oak Dr, CA"

CUSTOMER TABLE:

Customer_ID, Customer_Name

C001, Alice Johnson

C002, Bob Smith

C003, Charlie Davis

Order table with Order_ID as primary key (PK) and Customer table with Customer_ID as the primary key (PK) in the Customer table and as a foreign key (FK) in the Order table.