AI Data Engineer/ Data Scientist

Next Ventures; New Jersey; On-site; USD 120,000 - 190,000; Full time

Job summary

Next Ventures is seeking an AI Data Engineer / Data Scientist to build and support data products focused on patient journey optimization and pre-call intelligence. The role combines data engineering, feature engineering, and applied machine learning to create production-ready analytical solutions.

The ideal candidate will work with Snowflake, SQL, Python, and Dataiku, leveraging Snowpark or PySpark and a working knowledge of ML.

Qualifications

• Hands-on experience with Snowflake for data storage, transformation and analytics.
• Strong SQL skills for transforming data and feature engineering.
• Proficiency in Python for data processing and ML tasks.
• Experience with Snowpark or PySpark for data processing.
• Practical use of Dataiku for analytical workflows and model scoring.
• Familiarity with machine learning concepts and production data pipelines.

Responsibilities

• Data Engineering & Transformation: query, transform, and optimize data from Snowflake.
• Feature Engineering: build and maintain feature datasets and views.
• Dataiku Development: create and maintain analytical workflows in Dataiku.
• Machine Learning: design, build, validate, and support ML models.
• Feature Store Management: evaluate and maintain features for reuse.
• Data Product Support: develop analytics datasets for BI and decision-making.
• Data Quality & Reliability: implement testing, monitoring, and optimization.

Skills

Analytical thinking

Problem solving

Cross-functional collaboration

Tools

Snowflake

SQL

Python

Dataiku

Snowpark

PySpark

Job description

AI Data Engineer / Data Scientist

Snowflake | Dataiku | Machine Learning

Overview

We are seeking an AI Data Engineer / Data Scientist to help build and support data products focused on patient journey optimization and pre-call intelligence. This role combines data engineering, feature engineering, and applied machine learning to transform enterprise data into actionable insights and production-ready analytical solutions.

The ideal candidate has hands-on experience with Snowflake, SQL, Python, and Dataiku, along with Snowpark or PySpark experience and a working knowledge of machine learning. You will collaborate with data scientists and cross-functional teams to build reliable data pipelines, develop feature datasets, and support the delivery of scalable, data-driven products in a governed enterprise environment.

Key Responsibilities

• Data Engineering & Transformation: Query, transform, and optimize data from Snowflake, working with existing star-schema tables to support analytical and machine learning use cases.

• Feature Engineering: Build and maintain feature datasets, tables, and views in Snowflake to support downstream analytical workflows and model development.

• Dataiku Development: Create and maintain analytical workflows and features in Dataiku for use by data science teams and machine learning models.

• Machine Learning: Design, build, validate, and support machine learning models for patient journey optimization and pre-call intelligence use cases.

• Feature Store Management: Evaluate existing features in the Feature Store before creating new ones, promoting reuse and consistency across analytical products.

• Data Product Support: Develop and maintain analytical data products and reporting datasets that support business intelligence and decision-making.

• Data Quality & Reliability: Implement testing, validation, monitoring, and performance optimization practices to ensure data accuracy and pipeline reliability.

• Pipeline Support: Troubleshoot data issues and assist with upstream data pipelines and integrations as needed.

• Cross-Functional Collaboration: Partner with data scientists, data engineers, analytics teams, and business stakeholders to translate requirements into effective technical solutions.

Required Qualifications

• Hands-on experience with Snowflake for data storage, transformation, querying, and analytical data development.

• Strong SQL skills, including the ability to write and optimize complex queries for data transformation and feature engineering.

• Proficiency in Python for data processing, analytical workflows, and machine learning applications.

• Experience with Snowpark or PySpark for data processing and transformation.

• Practical experience with Dataiku for analytical workflows, feature development, model scoring, or machine learning processes.

• Familiarity with machine learning concepts and experience building, validating, or supporting ML models.

• Experience developing and maintaining production data pipelines and reusable datasets.

• Knowledge of data modeling, data quality testing, monitoring, and CI/CD practices.

• Ability to work effectively in a governed enterprise environment with established data standards and controls.

• Strong analytical, problem-solving, communication, and collaboration skills.

Preferred Qualifications

• Experience in healthcare, healthcare claims, patient support, provider data, or healthcare analytics.

• Familiarity with healthcare professional (HCP) data or Veeva platforms.

• Experience with AWS data services, including Lambda, S3, Glue, and Step Functions.

• Familiarity with feature stores, feature reuse, and production machine learning workflows.

• Experience with Power BI or other enterprise business intelligence and reporting tools.

• Experience supporting data products that drive predictive analytics, customer insights, or workflow optimization.

What We're Looking For

We are looking for a technically strong, hands-on professional who can bridge data engineering and data science. The ideal candidate is comfortable working across data transformation, feature development, and machine learning workflows, with a focus on building reliable, reusable, and scalable data products that deliver meaningful business value.