Senior Data Quality Assurance Specialist
1 day ago
We are seeking an experienced Data Quality Expert to lead and manage our data quality assurance efforts. As a key member of our team, you will be responsible for developing and implementing a comprehensive data quality strategy that aligns with our organizational objectives.
This is a leadership role that requires strong analytical skills, excellent communication skills, and the ability to work collaboratively with cross-functional teams. You will be responsible for defining standards and best practices for data quality assurance processes, leading efforts to profile and analyze data across systems, and establishing and enforcing data quality assurance processes.
Key Responsibilities:
- Develop and implement a comprehensive data quality strategy aligned with organizational objectives.
- Define standards and best practices for data quality assurance processes.
- Lead efforts to profile and analyze data across systems to identify issues related to accuracy, completeness, consistency, and timeliness.
- Establish and enforce data quality assurance processes, including data validation, cleansing, and monitoring.
- Design and implement data quality checks and controls.
- Define key performance indicators (KPIs) to measure data quality.
- Generate regular reports on data quality metrics and trends for stakeholders.
- Maintain documentation on data quality issues, resolutions, and improvements.
Required Skills:
- 10+ Years of Experience in Data Test Automation, Data Comparison and Validation.
- Strong understanding of data structures, databases, DB Procedures, Packages, and Functions.
- Familiarity with data quality tools and platforms for profiling, cleansing, and monitoring data.
- Proficient in SQL and scripting languages for data analysis and validation.
- Working experience with Python libraries such as Pandas, NumPy, and SQL Alchemy for ETL.
- Strong analytical skills to identify and solve data quality issues.
- Excellent communication skills to interact with cross-functional teams and stakeholders.
- Leadership skills to guide and inspire a team focused on data quality.
Bonus Requirements:
- Familiarity with big data technologies like Hadoop, Spark, and NoSQL databases can be beneficial.
- Proficiency in data visualization tools (e.g., Tableau, Power BI).
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