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.
Type of work model
Hybrid
Details to consider
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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