Data Engineer

Stone Alliance Group Career Page; New York (NY); On-site; USD 119,000 - 150,000; Full time

Benefits offered by this job

Medical insurance

401(k)

Paid parental leave

Dependent care

Flexible work schedules

Discounted tickets and entertainment

Job summary

Stone Alliance Group is seeking an experienced Data Engineer to join the Center for Data Analytics, Innovation, and Rigor in New York City. You will develop data pipelines, data infrastructure, and AI evaluation frameworks using Python, SQL, Docker, Kubernetes, AWS and Azure.

You will work in a hybrid setup, reporting to the Rubric Engineering and Measurement Specialist, with an in-office requirement of at least four days per week. This is a full-time exempt role based in NYC.

Qualifications

• Master's degree in Neuroscience, Psychology, Engineering, Computer Science or equivalent combination of education and experience is required.
• 5+ years of experience in data analysis and data science fundamentals (e.g., algorithms, data structures, data visualization, machine learning), preferably in a clinical or research setting.
• 5+ years of experience in at least one scientific programming language (e.g., Python/R, Matlab) and related toolboxes or frameworks (e.g., Tidyverse, Scipy, Sklearn, Polars, Pytorch) is required.
• 5+ years of experience working in a Linux environment, using version control systems (e.g., GitHub), and software virtualization platforms (e.g., Docker).
• 5+ years of practical experience in ETL processes and database management languages (SQL, NoSQL), and familiarity with associated cloud computing services and frameworks (AWS, Azure, Terraform).

Responsibilities

• Create and maintain scalable data pipelines for efficient storage and retrieval of multimodal data, with particular emphasis on clinical, natural language, and multi-turn response data.
• Create pipelines for data transformation, preprocessing, and management. Ensure data quality, security, and compliance with privacy regulations for handling sensitive data.
• Perform quality assurance of pipelines/processes to maintain integrity throughout the data lifecycle.
• Create interactive visualizations and dashboards to communicate data insights and pipeline performance metrics.
• Write documentation and relevant text for scientific, clinical, or public dissemination of knowledge.
• Perform additional job-related duties as assigned.

Skills

Data analysis

Data science fundamentals

Machine learning

Clinical/research data

Education

Master's degree in Neuroscience, Psychology, Engineering, Computer Science or equivalent

Tools

Python

R

Matlab

Tidyverse

Scipy

Sklearn

Polars

Pytorch

Linux

GitHub

Docker

Terraform

AWS

Azure

Job description

Our client is seeking an experienced Data Engineer to join their Center for Data Analytics, Innovation, and Rigor team in New York City.

As part of the Center for Data Analytics, Innovation, and Rigor team, you will report to the Rubric Engineering and Measurement Specialist. You will develop infrastructure to support large‑scale AI evaluation frameworks, design scalable data pipelines for generating and processing synthetic data, implement secure data storage solutions, and create infrastructure for real‑time model evaluation and monitoring. You will use common frameworks, platforms, and languages, such as Python, SQL, GitHub, containerization tools (e.g., Docker, Kubernetes), and cloud computing infrastructures (e.g., AWS, Azure) to build robust and scalable data infrastructure that supports our AI research initiatives.

This is an exempt, full‑time, hybrid position located in our NYC headquarters office or other relevant location. This position requires a minimum of four (4) days per week in the office, on a schedule determined by your supervisor. The in‑office requirement and schedule are subject to change based on the needs of the program and the organization.

Responsibilities

• Create and maintain scalable data pipelines for efficient storage and retrieval of multimodal data, with particular emphasis on clinical, natural language, and multi‑turn response data.
• Create pipelines for data transformation, preprocessing, and management. Ensure data quality, security, and compliance with privacy regulations for handling sensitive data.
• Perform quality assurance of pipelines/processes to maintain integrity throughout the data lifecycle.
• Create interactive visualizations and dashboards to communicate data insights and pipeline performance metrics.
• Write documentation and relevant text for scientific, clinical, or public dissemination of knowledge.
• Perform additional job‑related duties as assigned.

Qualifications

• Master's degree in Neuroscience, Psychology, Engineering, Computer Science or equivalent combination of education and experience is required.
• 5+ years of experience in data analysis and data science fundamentals (e.g., algorithms, data structures, data visualization, machine learning), preferably in a clinical or research setting.
• 5+ years of experience in at least one scientific programming language (e.g., Python/R, Matlab) and related toolboxes or frameworks (e.g., Tidyverse, Scipy, Sklearn, Polars, Pytorch) is required.
• 5+ years of experience working in a Linux environment, using version control systems (e.g., GitHub), and software virtualization platforms (e.g., Docker).
• 5+ years of practical experience in Extract, Transform, Load (ETL) processes and database management languages (SQL, NoSQL), and familiarity with associated cloud computing services and frameworks (AWS, Azure, Terraform).

Salaries & Benefits

The anticipated salary range for this position is $119,000 - $150,000 USD annually.

Our client’s competitive compensation and benefits include medical insurance, 401(k), paid parental leave, dependent care, flexible work schedules, discounted tickets and entertainment perks programs.

EEO Statement

Our client is an equal opportunity employer and does not discriminate in employment based on race, religion (including religious dress and grooming practices), color, sex/gender (including pregnancy, childbirth, breastfeeding or related medical conditions), sex stereotype, gender identity/gender expression/transgender (including whether or not you are transitioning or have transitioned) and sexual orientation; national origin (including language use restrictions and possession of a driver’s license issued to persons unable to prove their presence in the United States is authorized under federal law [Vehicle Code section 12801.9]); ancestry, physical or mental disability, medical condition, genetic information/characteristics, marital status/registered domestic partner status, age (40 and over), sexual orientation, military or veteran status, or any other basis protected by federal, state or local law or ordinance or regulation.