Senior Data Architect

1 day ago

Lahore, Punjab, Pakistan beBee Careers Full time

We are seeking a highly skilled Data Architect to design and implement our data infrastructure as we build AI-powered systems.

This role is centered on solving data-centric challenges, from transforming and migrating data to ensuring consistency, integrity, and scalability across systems.

The ideal candidate will have a deep understanding of data engineering principles, a strong command over Python, and experience working with MongoDB and knowledge graph technologies.

Key Responsibilities:

  • Data Pipeline Design
  • Migrate and maintain data in knowledge graph databases (e.g., Neo4j, TigerGraph), ensuring alignment with evolving schema and AI use cases.
  • Data Validation and Integrity
  • Ensure data correctness and consistency across all stages of the pipeline by implementing rigorous validation, monitoring, and fallback mechanisms.
  • Error Handling and Recovery
  • Handle failure gracefully in pipelines with proper alerting, retries, and state recovery strategies to maintain reliability and uptime.
  • Collaboration with AI Teams
  • Collaborate with AI teams to structure data for Graph RAG-based context retrieval, enhancing the effectiveness of LLM-driven modules.
  • Utility Development
  • Develop utilities and tools in Python to support data manipulation, export/import routines, and graph schema enforcement.
  • Ontology and Data Model Design
  • Contribute to ontology and data model design to reflect domain knowledge in structured, queryable forms.

Required Skills and Qualifications:

  • Strong proficiency in Python, especially for data processing and automation.
  • Solid foundation in data structures, algorithms, and software design principles.
  • Experience with MongoDB and handling large-scale semi-structured data.
  • Familiarity with knowledge graph databases (e.g., Neo4j, TigerGraph) and graph data models.
  • Understanding of ETL processes, data validation, and pipeline orchestration.
  • Proven ability to assure data correctness and manage failure cases in real-world data systems.
  • Basic knowledge of AI concepts, especially LLMs and Retrieval-Augmented Generation.

Preferred Qualifications:

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Statistics, or a related field.
  • Experience working with large datasets and modern data tools (like Airflow, dbt, Spark, etc.).
  • Previous experience supporting data science, analytics, or machine learning teams.

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