Senior Software Engineer (Data Engineering)

TL;DR

Senior Software Engineer (Data Engineering): Designing, building, and maintaining scalable data architectures, data models, and ETL/data pipelines with an accent on performance optimization, data quality & governance, and production reliability. Focus on integrating diverse sources into a unified data platform and collaborating across data science, analytics, and engineering to deliver data within defined SLAs.

Location: Remote, USA

Salary: $179,400 - $224,300 (base compensation range)

Company

hirify.global builds virtual-first healthcare technology for chronic disease management using connected devices and AI-enabled care.

What you will do

• Design and implement scalable, secure, and efficient data architectures and engineering data models.
• Build and optimize ETL processes and data pipelines to ensure smooth data flow from multiple sources.
• Integrate APIs, databases, and third-party data into a unified data platform.
• Monitor and optimize data system and pipeline performance for low latency and high throughput; deliver data within defined SLAs.
• Implement data quality checks, validation, and governance frameworks to ensure accuracy and reliability.
• Collaborate with data scientists, analysts, product, and engineers; document architectures and train teammates on data engineering best practices.

Requirements

• 5+ years building, maintaining, and orchestrating scalable data pipelines.
• 3+ years as a data engineer developing or maintaining integrations using Airflow or Python-based data pipeline code.
• Strong SQL skills and experience with relational databases (e.g., MySQL, PostgreSQL) and analytical SQL on MPP systems (e.g., Redshift, BigQuery, Snowflake).
• Experience with data modeling for OLTP and OLAP applications.
• Experience with cloud platforms such as Amazon AWS; familiarity with workflow management tools (Airflow preferred) and cloud data warehouses (Redshift preferred).
• Experience working with sensitive data (PHI/PII) and applying security best practices; familiarity with data governance practices.

Culture & Benefits

• Remote-first work from home culture.
• Flexible Time Off and generous parental leave.
• Health, dental, and vision insurance with above-market employer contributions.
• 401k retirement savings plan and Lifestyle Spending Account (LSA).
• Annual cash bonus eligibility and equity grants.
• Mental health support solutions.

Hiring process

• Interviews focused on data engineering experience, system design, and collaboration.
• Evaluation of technical depth in data pipelines, SQL, and performance/data quality practices.
• Discussion of role scope, expectations, and fit across cross-functional stakeholders.