Data Engineer (Pipelines & Vector Databases)

Company OverviewOur 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 OverviewWe 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 ResponsibilitiesBuild and maintain data pipelines across multiple sourcesDesign data processing, transformation, and storage systemsCreate and maintain a canonical data layerEnsure data quality, consistency, and reliabilityStructure datasets for both product and AI use casesSupport vector databases and AI data workflowsRequirementsStrong experience in data engineering and pipeline developmentHands-on experience with Airflow, Dagster, dbt (or similar)Strong knowledge of data modeling and transformationExperience working with large, complex datasetsAbility to build scalable and reliable data systemsPreferred QualificationsExperience with vector databases (Pinecone, PgVector)Familiarity with embeddings, retrieval systems, or AI data layersExposure to modern AI data tools (e.g., MindsDB)What This Role Focuses OnData ingestion, transformation, and pipeline reliabilityBuilding structured, trusted datasetsSupporting AI and product systems with high-quality dataKey TraitsStrong attention to detail and data qualitySystems thinker with scalability mindsetComfortable working with high-volume, complex data