Senior Data Engineering Professional

4 days ago

Guntur, Andhra Pradesh, India beBeeDataQuality Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

**Job Overview:**

We are seeking a seasoned professional to assume the role of Data Engineering Lead. This position requires a deep understanding of data pipelines, data validation, and AI-enhanced quality frameworks.

This individual will be 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).
  • 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.
  • Ensure auditability and traceability of decisions derived from enriched or corrected data.

**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/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.

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