
Leading Data Engineer
3 hours ago
**Job Description – Data Engineering Lead (AI for Data Quality & Analytics)**
Experience Overview:
We are seeking an experienced data engineering professional with a strong foundation in data pipelines, data validation, and AI-enhanced quality frameworks. This role is responsible for building and maintaining 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.
Main Responsibilities:
- Data Quality Management
- Design and implement scalable data quality validation systems across multiple sources.
- Develop AI-driven tools that identify anomalies, detect irrational transactions, and provide early insight into data discrepancies.
- Engineering & 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.
- Collaborate with business analysts to incorporate predictive insights and pattern recognition from historical data anomalies.
- Data Governance & Reporting
- Partner with stakeholders to proactively identify and address reporting gaps or escalations.
- Cross-Functional Collaboration
- Work closely with business analysts, data scientists, and engineering teams to align system architecture with business needs.
- Educate and influence non-technical business users on the importance of data quality and automated anomaly detection.
Key Qualifications:
- 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/ML in data quality (anomaly detection, NLP-driven validation, etc.).
- Familiarity with enterprise systems like Workday, Beeline, and custom Excel-based reporting.
- Strong interpersonal and communication skills to work with executive stakeholders and distributed teams.
Preferred Attributes:
- Experience leading data modernization or AI transformation projects.
- Prior exposure to dashboard adoption challenges and enterprise change management.
How to Apply:
- Please submit your updated resume.
- Include relevant information such as total experience, relevant experience, current compensation, expected compensation, and notice period.
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