Job Title: Data EngineerDepartment: Department of Health and Mental HygieneDivision: Center for Population Health and Data ScienceBureau: Data Technology and StrategyLocation: 42-09 28th St, Long Island City, NY 11101 Reports to Title: Mark AlexanderDirect Reports Title(s): Data ScientistSchedule & Hours: M-F, 9am -5pm ; 35 hours per week;Workplace Flexibility Modality: Hybrid, 3 days in officeWork Environment: Office Environment, occasional travel for meetings and presentations within the NYC boroughs. Grant End Date: 6/30/2027Created Date: 6/4/2026Revised Date: N/ASalary: $125,000 - $128,000FLSA Classification: ExemptProgram Overview
The Center for Population Health Data Science (CPHDS)- launched in October of 2023- aims to catalyze critical data modernization work and enable the agency to make progress toward linking public health, healthcare, and social service for timely and effective public action. We are working towards making these data more accessible, timely, equitable, meaningfully usable, and protected and actively used to protect and promote the health and wellbeing of New Yorkers. We aim to strengthen agency wide data capabilities by empowering our workforce, enhancing intra- and inter-agency data sharing, and using modern technology to yield trusted and integrated data and insights. A real-time and comprehensive view of city needs is needed to enhance public health actions and improve health outcomes for the most vulnerable New Yorkers.
POSITION OVERVIEW
We are seeking to fill data engineer positions for integrating and analyzing data collected across critical agency systems. It is expected that each position will work 35 hours per week.
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
QUALIFICATIONS
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
PREFERRED SKILLS:
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
Benefits/ Additional Information:- 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
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