Senior Data Engineer

Enzo Tech Group; United States; On-site; USD 100,000 - 130,000; Full time

Job summary

A growing healthcare data firm in the United States is seeking an experienced Data Engineer with a strong background in AWS Glue and Spark/PySpark. The role involves architecting and optimizing ETL pipelines, maintaining S3 data lake structures, and ensuring data governance standards. Candidates should have over 5 years of experience in data engineering and familiarity with healthcare data environments. This is an opportunity to lead platform-level engineering work in a secure environment.

Qualifications

• 5+ years of experience in Data Engineering required.
• Strong capability with Spark/PySpark necessary.
• Experience with regulated datasets and Healthcare environments preferred.

Responsibilities

• Architect and optimize AWS Glue ETL pipelines.
• Build and maintain scalable S3 data lake structures.
• Design and tune Redshift warehouse environments.
• Drive data quality, governance, and reliability standards.

Skills

AWS Glue ETL pipelines

Data Engineering

Spark/PySpark

Data Governance

Tools

Amazon S3

Amazon Redshift

Python

SQL

Terraform

Job description

If you’ve built real, production-grade AWS Glue pipelines — not just experimented with them — this is the kind of role that lets you own it properly.

We’re partnering with a growing Healthcare / PBM (Pharmacy Benefit Management) organization investing heavily in its AWS data platform. Glue is the backbone. This isn’t maintenance work — it’s platform-level engineering handling large-scale pharmacy and claims data in a secure, HIPAA-aware environment.

What You’ll Be Doing:

• Architect and optimize AWS Glue ETL pipelines (Jobs, Crawlers, Workflows, Data Catalog)
• Build and maintain scalable S3 data lake structures
• Design and tune Redshift warehouse environments
• Implement efficient partitioning and performance optimization strategies
• Handle large-scale pharmacy and claims datasets
• Drive data quality, governance, and reliability standards
• Partner with analytics, clinical, and product stakeholders to deliver trusted data assets
• Influence architecture decisions and long-term platform direction

Core Tech Stack:

• PySpark / Spark
• Amazon S3
• Amazon Redshift
• Python & SQL
• Infrastructure-as-Code exposure (CDK or Terraform a strong plus)

What We’re Looking For:

• 5+ years in Data Engineering
• Strong Spark/PySpark capability
• Experience working with large, regulated datasets
• Background in Healthcare, PBM, payer, or insurance data environments preferred
• Comfortable owning architecture — not just executing tickets