
Data Quality Architect
10 hours ago
We are seeking an experienced professional to lead our data quality initiatives.
This role is responsible for designing and implementing high-quality data ingestion and validation processes from multiple upstream systems, while laying the foundation for AI-driven anomaly detection, business insight extraction, and scalable reporting solutions.
Key Responsibilities:- Data Validation and Governance
- Develop and implement scalable data quality validation systems across multiple sources.
- Collaborate with stakeholders to identify and address reporting gaps or escalations.
- Data Engineering and Automation
- Lead development of data pipelines and validation scripts using Python, Alteryx, and integration into reporting tools.
- Implement pre-processing checks for incoming files to detect issues before ETL pipelines are executed.
- AI and Machine Learning Integration
- Build and deploy AI models to automate issue detection, enhance data lineage tracking, and generate intelligent alerts on unexpected changes.
- Educate and influence non-technical stakeholders on the importance of data quality and automated anomaly detection.
- Cross-Functional Collaboration
- Work closely with business analysts, data scientists, and engineering teams to align system architecture with business needs.
- Mentor junior engineers and analysts to optimize team performance.
- Technical Expertise
- 6–10 years of experience in data engineering, data quality, or analytics engineering roles.
- Proficient in Python, Alteryx, SQL, and cloud data platforms like Snowflake.
- Deep understanding of data pipelines, ETL/ELT processes, and data validation best practices.
Preferred Qualifications:
- Experience with AI/ML in data quality (anomaly detection, NLP-driven validation, etc.).
We offer a competitive compensation package, comprehensive benefits, and opportunities for growth and development. If you're passionate about delivering high-quality data solutions, we encourage you to apply for this exciting opportunity.
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