AI Data Engineer

C the Signs

full-time

Posted on: 9/24/2025

Origin: • 🇺🇸 United States • Massachusetts

✨ AI Apply

Mid-LevelSenior

AirflowApacheAWSAzureCloudETLGoogle Cloud PlatformJavaPythonScalaSpark

About the role

Collaborate with data scientists and machine learning engineers to understand data requirements for LLM and machine learning model fine-tuning.
Design, build, and maintain scalable data pipelines to ingest, process, and store massive and diverse healthcare datasets.
Implement robust data validation and monitoring to ensure the integrity, accuracy, and consistency of all training datasets.
Implement robust data cleaning, validation, and transformation processes to ensure data quality and integrity.
Develop and optimize data structures and schemas for efficient access and utilization by LLMs and machine learning models.
Work with the team to identify and acquire new data sources, ensuring compliance with relevant healthcare regulations (e.g., HIPAA).
Monitor data pipeline performance, troubleshoot issues, and implement optimizations to improve efficiency and reliability.
Document data engineering processes, data models, and data dictionaries.
Stay up-to-date with the latest advancements in data engineering, big data technologies, and machine learning.

Bachelor's degree in Computer Science, Engineering, or a related field.
Proven experience as a Data Engineer, with a focus on big data technologies.
Strong proficiency in programming languages such as Python, Scala, or Java.
Extensive experience with data warehousing, ETL processes, and data modeling.
Experience with major cloud providers (e.g., AWS, GCP, Azure) and their data storage and processing services.
Hands-on experience with big data frameworks like Apache Spark for distributed processing.
Excellent problem-solving skills and the ability to work independently and as part of a team.
Strong communication and interpersonal skills.
Preferred: Master's degree in a related field.
Preferred: Experience with healthcare data and a good understanding of healthcare data standards (e.g., FHIR, HL7).
Preferred: Familiarity with machine learning concepts and LLM fine-tuning processes.
Preferred: Experience with data orchestration tools (e.g., Apache Airflow).