
Leading Data Engineer
13 hours ago
The primary objective of this senior-level position is to design, build, and maintain high-quality data pipelines and validation processes. In this capacity, the successful candidate will have an extensive understanding of scalable data quality management systems.
Key Responsibilities:
- Develop and implement robust data quality validation systems across multiple sources using Python, Alteryx, and integration into reporting tools.
- Collaborate with business analysts to develop predictive insights and pattern recognition from historical data anomalies.
- Work closely with business analysts, data scientists, and engineering teams to align system architecture with business needs.
- Lead a distributed team of engineers and analysts, providing guidance and mentorship.
Requirements:
- 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.
- Experience with AI-driven anomaly detection and NLP-driven validation techniques.
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