Top Remote Artificial Intelligence Data Engineering Jobs

The Analytics Engineer will enhance BI infrastructure, collaborate with Data Engineering, and deliver analytics-ready data. Responsibilities include managing Snowflake, dbt projects, and CI/CD workflows, optimizing data structures, and supporting BI initiatives.

As a Data Engineer, you will design and maintain data infrastructure, build ingestion pipelines, and collaborate with ML and product teams for data-driven features.

As an Associate Technical Architect, you will solve big data problems and develop solutions for migration, storage, and processing, focusing on Databricks and data engineering.

The role involves architecting intelligence infrastructure, building data pipelines, collaborating with other teams, and ensuring data accessibility and security for threat detection systems.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

As a Senior Clinical Data Engineer, you'll oversee clinical data lifecycles, manage data integrity, collaborate with project teams, and optimize data management processes for clinical trials.

The Founding Data Engineer will design and build OpenArt's core data platform, ensuring data reliability, consistency, and scalability to support leadership and product metrics.

The role involves managing data pipelines for AI and quantitative research, focusing on L3 market data architecture and integrity, API development, and collaboration with researchers.

The Senior Data & Analytics Engineer will design and maintain data pipelines, develop analytics schemas, build visualizations, and perform deep-dive analyses to drive business decisions.

Design and implement real-time and batch data pipelines (MQTT/Redpanda, Dagster), parse binary message formats, build data warehouses (Postgres, Iceberg, Parquet, S3), design high-performance data models, validate and normalize sources, and improve local development and CI/CD with GitHub Actions to support maritime domain awareness and defense-related AI workloads.