Data Engineering Lv.4

• →Build and manage analytics and production data ETL/ELT systems for high volume data ingestion from diverse
  sources. 
• →Partner with Data Science, Engineering, and Product to enable reliable, accurate logging/implementation and usage
  across the PPE domain.
• →Ensure data quality, observability, and reliability across the data lifecycle.
• →Create and maintain dashboards and reporting infrastructure to surface key PPE metrics to stakeholders.
• →Optimize systems for performance, cost efficiency, and scalability. 
• →Leverage LLMs and advanced prompt engineering to automate and extract insights from unstructured data, and
  accelerate internal analytical workflows.
• →Define and manage SLAs for data systems.

Basic Qualifications

• →3+ years of relevant working experience in a data engineering or business intelligence role.
• →Proficiency in Data modelling, SQL and Python.
• →Experience building and maintaining data pipelines (ETL/ELT) at scale.
• →Experience in data storytelling using PowerBI, Tableau, or similar tools to communicate insights effectively to nonexperts
• →Bachelor’s degree in Computer Science or equivalent.

Preferred Qualifications

• →Hands-on experience with version control (GitHub), workflow orchestration, and ETL scheduling tools (e.g. Airflow,
  Dagster, DBT).
• →Experience with distributed storage systems (e.g., HDFS, S3).
• →Familiarity with prompt engineering and using generative AI tools to solve data problems or automate content
  generation.
• →Previous experience in e-commerce or retail domains.
• →Working knowledge of statistics and ML techniques.

• Hybrid 

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

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