Job Title: Data Engineering Lead (AI for Data Quality & Analytics) Location: Bangalore Experience: 7 to 10 Years Notice Period : Immediate Job Summary: Role Overview We are seeking an experienced Data Engineering Lead 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. Key Responsibilities Data Quality Management Design and implement scalable data quality validation systems across multiple sources (e.g., Workday, Snowflake, Beeline, Excel logs). 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 (Fletcher, Aliana, etc.) to proactively identify and address reporting gaps or escalations. Ensure auditability and traceability of decisions derived from enriched or corrected data. Cross-Functional Collaboration Work closely with business analysts, data scientists, and engineering teams across India and the U.S. to align system architecture with business needs. Educate and influence non-technical business users on the importance of data quality and automated anomaly detection. Team Leadership & Optimization Lead a small, distributed team, mentoring junior engineers and analysts. Optimize headcount through AI augmentation, enabling skilled team members to focus on higher-value initiatives. 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: Send your updated resume to:
Job Title
Data Engineering Lead (AI for Data Quality & Analytics)