AI Data Engineer

Emmes Group•Rockville, MD

4h•Remote

About The Position

Veridix AI is the technology, data, and AI arm of the Emmes Group, a leading full-service contract research organization (CRO) with over 47 years of experience in supporting clinical research across more than 70 countries. With industry-leading capabilities in cell and gene therapy, vaccines, infectious diseases, and ophthalmology, Emmes is one of the top clinical service providers to the U.S. government and is rapidly expanding its presence in biopharma. Veridix AI develops advanced eClinical solutions, powering clinical trials through patient data collection, randomization, biospecimen tracking, and data quality monitoring. Our cutting-edge AI innovations, including Generative AI (GenAI) capabilities, are transforming clinical trial timelines by streamlining processes from document authoring to automating study builds. Our “Character Achieves Results” culture is driven by five key values that guide our actions in the way we conduct research and distinguish us as an organization: Integrity, Agility, Passion for Excellence, Collaborative Partnerships and Intellectual Curiosity. If you share our motivations and passion in research, come join us! You will be joining a collaborative culture that empowers every Emmes employee — from entry level through top executive — to contribute to our clients’ success by sharing ideas openly and honestly.

Requirements

Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
3 or more years of related professional experience.
Experience in data engineering strong focus on AWS cloud services.
Proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL, Redshift).
Experience with AWS services such as S3, Lambda, Glue, EMR, Kinesis, and Redshift.
Strong programming skills in languages such as Python, Java, or Scala.
Knowledge of data modeling, ETL concepts, and data warehousing.
Familiarity with version control systems (e.g., Git) and CI/CD pipelines.
Excellent problem-solving skills and attention to detail.
Knowledge of machine learning frameworks and data science workflows.
Familiarity with data visualization tools (e.g., QuickSight, Qlik).
Familiarity with NoSQL databases (e.g., DynamoDB, MongoDB).
Strong collaboration skills with cross-functional teams to establish best design and user flows for applications.
Strong multitasking, problem solving, and organizational skills.
Proven ability to work independently and in a team environment.
Satisfactory background check required.

Responsibilities

Design, develop, and maintain robust data pipelines and ETL processes to ingest, transform, and store data from various sources.
Collaborate with data scientists, analysts, and other stakeholders to understand data requirements, design data models, and deliver solutions that meet business needs.
Automate data workflows and implement monitoring and logging to ensure the health and performance of the data infrastructure.
Conduct data profiling, cleansing, and validation to ensure high data quality standards.
Optimize data storage and retrieval performance, ensuring data quality and integrity.
Implement and manage data architecture on AWS, ensuring scalability, reliability, and security.
Stay up to date with the latest trends and best practices in data engineering and AWS cloud technologies.