AI Data Engineer: Patient Journey & ML Pipelines

Sentior, Ltd.; United States; On-site; USD 55,000 - 83,000; Part time

Job summary

Sentior, Ltd. is seeking an AI Data Engineer / Data Scientist in the United States to build and support data products focused on patient journey optimization and pre-call intelligence.

You will work with Snowflake, SQL, Python, and Dataiku to develop production-ready analytical solutions and scalable data pipelines. The role emphasizes feature engineering, model development, feature store management, and cross-functional collaboration in a governed enterprise environment.

Qualifications

Responsibilities

• Query and transform data from Snowflake to support analytical and ML use cases.
• Build and maintain feature datasets, tables, and views in Snowflake for downstream workflows and models.
• Create and maintain analytical workflows and features in Dataiku for data science teams and ML processes.
• Design, validate, and support ML models for patient journey optimization and pre-call intelligence use cases.
• Evaluate existing features in the Feature Store and promote reuse across analytical products.
• Develop and maintain analytical data products and reporting datasets to support BI and decision-making.
• Implement testing, validation, monitoring, and performance optimization for data pipelines.
• Troubleshoot data issues and assist with upstream pipelines and integrations as needed.
• Collaborate with data scientists, engineers, analytics teams, and business stakeholders to translate requirements into technical solutions.

Skills

Snowflake

SQL

Python

Dataiku

PySpark

Snowpark

Machine Learning basics

Data pipelines

Data modeling

CI/CD

Tools

Dataiku

Snowpark

PySpark

AWS Lambda

S3

Glue

Step Functions

Power BI

Job description

Sentior, Ltd. is seeking an AI Data Engineer / Data Scientist in the United States to build and support data products focused on patient journey optimization and pre-call intelligence.

You will work with Snowflake, SQL, Python, and Dataiku to develop production-ready analytical solutions and scalable data pipelines. The role emphasizes feature engineering, model development, feature store management, and cross-functional collaboration in a governed enterprise environment.