Chief Data Architect

2 weeks ago

Varanasi, Uttar Pradesh, India beBeeDataEngineering Full time ₹ 25,00,000 - ₹ 30,00,000

As a pioneering Data Engineering Lead, you will be responsible for spearheading the development and maintenance of high-quality data ingestion and validation processes.

Job Overview

This role demands an exceptional blend of technical expertise and leadership skills to design, implement, and optimize scalable data pipelines and AI-enhanced quality frameworks.

Main Responsibilities:
  • Data Quality Management: Develop and execute comprehensive data quality validation systems across multiple sources, ensuring seamless integration and high-fidelity data lineage tracking.
  • Engineering & Automation: Create cutting-edge AI-driven tools to identify anomalies and provide early insight into data discrepancies, empowering informed decision-making.
  • Ai and Machine Learning Integration: Build and deploy robust AI models to automate issue detection, enhance data tracking, and generate intelligent alerts on unexpected changes.
  • Cross-Functional Collaboration: Collaborate closely with business analysts, data scientists, and engineering teams to align system architecture with business needs and drive strategic initiatives.
Leadership and Optimization:
  • Lead a distributed team of skilled engineers and analysts, mentoring junior professionals and driving innovation.
  • Optimize headcount through AI augmentation, enabling team members to focus on high-value initiatives and drive exponential growth.
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.).

To excel in this role, you will require strong interpersonal and communication skills, as well as the ability to collaborate effectively with cross-functional teams and communicate complex ideas to executive stakeholders.

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