Data Engineer - AWS

Position: Data Engineer - AWS

Location: Hybrid (Must Reside in NY/NJ/CT)

Work Schedule: Monday - Friday, 9:00am - 5:00pm

Compensation: $118,135.58 - $132,902.53 Annual Salary

VillageCare is a community-based, not-for-profit organization serving people with chronic care needs, as well as seniors and individuals in need of continuing care and managed care services.

Our mission is to promote healing, better health and well-being to the fullest extent possible. Our care is offered through a comprehensive array of community and residential programs, as well as managed care. VillageCare has delivered quality health care services to individuals residing within New York City for over 45 years.

As a Data Engineer, you will strengthen VillageCare's cloud data foundation by advancing reliable, secure data movement and analytics-ready datasets in our AWS environment. This role exists to ensure stakeholders can trust and use data to support care and operations.

Key responsibilities:
- Design, build, and support ELT/ETL pipelines and datasets within an AWS Data Lake
- Monitor and tune AWS data lake services; troubleshoot analysis tooling in the cloud environment
- Build Python-based ETL jobs; develop light internal web tools as needed
- Model current and future schemas for structured/unstructured data; align to industry standards
- Provide technical oversight across vendors; partner with IT Security/Network Ops on AWS best practices
- Contribute to integration project scoping and new pipeline/component design

Required qualifications:
- AWS (2+ yrs), SQL (5+ yrs), Python (2+ yrs); Postgres/MySQL (2+ yrs), Redshift (2+ yrs)
- Healthcare data experience (2+ yrs) and awareness of Provider/Payer/Member domains
- AWS Glue, Spark, Lambda/API Gateway, containers, Git, Jira

- Minimum of Bachelors Degree in technical field (Computer Science, Management Information Systems, Statistics or analytics. Masters preferred

Apply to help deliver dependable data engineering outcomes for VillageCare.

Your day is organized around steady progress and clear communication. You start by reviewing overnight pipeline health and AWS service metrics, then confirm priorities with project partners and vendor teams. Midday is often reserved for focused build time-iterating on a new dataset, validating transformations, or refining a schema so downstream reporting behaves consistently. You'll also field targeted questions from end users, translating business needs into concrete technical decisions, and you'll document choices so others can follow the logic. Later, you may join a working session with Security and Network Operations to align on cloud requirements, then close out by updating Jira items and pushing well-tested changes through GitHub. The schedule supports work-from-home flexibility while keeping delivery predictable.