Data Engineer: Build Scalable Pipelines & Data Quality

Garner Health; New York (NY); Hybrid; USD 120,000 - 170,000; Full time

Benefits offered by this job

Flexible PTO

Hybrid and remote work

Team meets twice yearly

401(k) with company match

Job summary

Garner Health is seeking a data engineer to build and optimize data pipelines, create reusable data sets for BI and data science, and develop a federated data validation framework. The role emphasizes privacy, security, and HIPAA-aware practices within a high-velocity, mission-driven team.

You will work in a hybrid/remote setting, collaborating across product, analytics, and engineering to ensure data quality and governance for healthcare data workflows.

Qualifications

• 2+ years of software/data engineering experience.
• Expertise in building scalable data pipelines.
• Experience with SQL and Python.
• Familiarity with HIPAA compliance.

Responsibilities

• Build, optimize, and maintain data pipelines that power our business.
• Define and build out abstracted reusable data sets for BI, marketing, and data science.
• Design, build, and evangelize a federated data validation framework to monitor data inconsistencies.
• Protect users’ privacy and security through best practices.

Skills

Airflow

PostgreSQL

Snowflake

SQL

Python

Data pipelines

Job description

Garner Health is seeking a data engineer to build and optimize data pipelines, create reusable data sets for BI and data science, and develop a federated data validation framework. The role emphasizes privacy, security, and HIPAA-aware practices within a high-velocity, mission-driven team.

You will work in a hybrid/remote setting, collaborating across product, analytics, and engineering to ensure data quality and governance for healthcare data workflows.