Company Overview
Our client is a fast-growing technology company building scalable, data-intensive systems that power both product experiences and AI-driven capabilities. Their platform relies heavily on clean, structured, and reliable data to enable advanced features, automation, and intelligent decision-making.
They are investing in modern data infrastructure to support both core product functionality and emerging AI use cases, ensuring that data is accessible, accurate, and optimized for scale.
Role Overview
We are looking for a full-time (40 hours/week) Senior Data & AI Infrastructure Engineer to design and build the data backbone of our platform.
This role focuses on data pipelines, transformation, and infrastructure, ensuring that data from multiple sources is ingested, structured, and made reliable for both product and AI systems.
You will work in the EST time zone, collaborating with engineering teams to support scalable data systems and enable AI-driven functionality.
Key Responsibilities
* Build and maintain data pipelines across multiple sources
* Design data processing, transformation, and storage systems
* Create and maintain a canonical data layer
* Ensure data quality, consistency, and reliability
* Structure datasets for both product and AI use cases
* Support vector databases and AI data workflows
Requirements
* Strong experience in data engineering and pipeline development
* Hands-on experience with Airflow, Dagster, dbt (or similar)
* Strong knowledge of data modeling and transformation
* Experience working with large, complex datasets
* Ability to build scalable and reliable data systems
Preferred Qualifications
* Experience with vector databases (Pinecone, PgVector)
* Familiarity with embeddings, retrieval systems, or AI data layers
* Exposure to modern AI data tools (e.g., MindsDB)
What This Role Focuses On
* Data ingestion, transformation, and pipeline reliability
* Building structured, trusted datasets
* Supporting AI and product systems with high-quality data
Key Traits
* Strong attention to detail and data quality
* Systems thinker with scalability mindset
* Comfortable working with high-volume, complex data