10101 - Data Engineer

Fund for Public Health NYC • Queens, NY

17d • Hybrid

About The Position

The Fund for Public Health in New York City (FPHNYC) is a 501(c)3 non-profit organization dedicated to advancing the health and well-being of all New Yorkers. In partnership with the New York City Department of Health and Mental Hygiene (DOHMH), FPHNYC incubates innovative public health initiatives. The Center for Population Health Data Science (CPHDS), launched in October 2023, aims to catalyze critical data modernization work, enabling the agency to link public health, healthcare, and social services for timely and effective public action. The goal is to make data more accessible, timely, equitable, usable, and protected, and to actively use it to promote the health and well-being of New Yorkers. This involves strengthening agency-wide data capabilities by empowering the workforce, enhancing data sharing, and using modern technology to yield trusted and integrated data and insights. A real-time and comprehensive view of city needs is essential to enhance public health actions and improve health outcomes for vulnerable New Yorkers. We are seeking to fill data engineer positions for integrating and analyzing data collected across critical agency systems. Each position is expected to work 35 hours per week.

Requirements

• 3+ years of hands-on experience with Python version 3.x
• 3+ years of hands-on experience with SQL databases
• 3+ years of hands-on experience with mathematical, statistical, machine learning, or artificial intelligence models in Python
• 2+ years of hands-on experience performing data science tasks using cloud-based technologies
• 2+ years of experience building Python applications that leverage cloud-based technologies such as docker or Azure Container Apps or Azure App Service
• 3+ years of Data Lake analytics platforms such as Azure Synapse or Databricks
• Strong organization and time management skills
• Good written and verbal communication skills
• Ability to work independently as well as part of a team
• Undergraduate degree or certificate in Data Science, Mathematics, Applied Mathematics, Statistics, Applied Statistics, Computer Science, Computer Engineering, Electrical Engineering, Physics, or a similar field of study

Nice To Haves

• 5+ years of experience performing data science tasks using cloud-based technologies
• 5+ years of hands-on experience in Python
• 3+ years of experience building applications in Python web frameworks such as FastAPI, Django, or Flask
• 3+ years of experience using ETL platforms such as Azure Data Factory or Airflow
• Graduate degree in Data Science, Mathematics, Applied Mathematics, Statistics, Applied Statistics, Computer Science, Computer Engineering, Electrical Engineering, Physics, or a similar field of study

Responsibilities

• Provide data engineering and infrastructure configuration support for complex Python applications
• Aid migration of complex Python applications from on-premise environments to Azure including transformation of applications to cloud native architecture
• Build and oversee automated data extraction, transfer, and load processes to support analytics databases
• Build resources to ingest, extract, or analyze data housed in a data lake environment
• Design, build, and document scalable hybrid technology architecture using both on-premise and cloud resources on Azure
• Identify, explore, and help build emerging free, open source technologies
• Design, implement, test, deploy, update, and document statistical, machine learning, and deep learning models
• Propose and implement improvements to the DOHMH data science infrastructure and processes

Benefits

• Public Service Loan Forgiveness (PSLF) eligible employer
• Generous Paid Time Off (PTO) policy
• Medical, dental, and life insurance with low or no employee contribution
• A retirement savings plan with generous employer contribution
• Flexible spending medical and commuter benefits plan
• Meaningful work at an organization striving to advance health equity and social justice

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Associate degree