Data Engineer, GenAI Data Systems

• Bachelor’s Degree in Computer Science or related engineering field, or equivalent experience.
• 4+ years of professional experience in data engineering or a closely related field.
• Experience designing, building, and operating production ETL/ELT pipelines for large, complex datasets.
• Strong SQL and Python proficiency for data pipelines, automation, and production software.
• Familiarity with CI/CD, testing frameworks, and version control (e.g., Git).
• Experience with workflow orchestration (e.g., Airflow, Dagster, or Databricks Jobs/Lakeflow).
• Demonstrated experience designing and maintaining data models, data pipelines, and databases (relational and/or lakehouse/warehouse).
• Experience designing and operating high-volume logging or telemetry systems, with a focus on efficiency and monitoring.
• Experience building and maintaining dashboards, reports, and alerting, and keeping metric definitions accurate over time.
• Hands-on experience with Databricks, Spark, Delta Lake, or similar lakehouse/big-data platforms.
• Experience with a major cloud platform (AWS, Azure, or GCP) and large-scale storage systems.
• Proficiency using AI tools for coding and data tasks, paired with strong first-principles reasoning about design, coding, and datasets - 8+ years of experience in data engineering or analytics engineering.
• Experience building data pipelines specifically for annotation projects running in annotation platforms (human-in-the-loop / labeling workflows).
• Direct experience with SuperAnnotate.
• Experience supporting LLM/VLM or other ML model training data pipelines.
• Experience working with large-scale, high-volume, multi-modal datasets (e.g., text, image, video, audio), with attention to storage and processing efficiency.
• Front-end or full-stack experience (JavaScript/TypeScript/HTML) for internal tooling and lightweight data/annotation UIs.

Insight Global is looking for a Data Engineer, GenAI Data Systems for one of our largest customers in the Bay Area who will hit the ground running on Data Engineering work, and someone who can contribute broadly across a variety of operational engineering tasks, not just traditional data pipeline development.

This role can pay between $75-$105 depending on years of experience and skillset.