Data Scientist Engineer

About Aloha

We’re proud to say that Aloha has been on the INC 5000 list for five consecutive years (2020-2024) We’re a leading SaaS health-tech company dedicated to providing innovative solutions that elevate the patient experience for healthcare providers. Our mission is to drive growth and advance innovation in the healthcare industry, and we’re on the lookout for passionate and driven team members to join our awesome team. Check out our products HERE

We're planning to keep the momentum going and are gearing up for our biggest growth spurt yet. Are you ready to join us? CLICK HERE to Meet our Team!

Why join Aloha?

• Fully remote opportunity
• 4 Company Provided Lunches Weekly
• Employer-paid Medical, Dental, and Vision Health Benefits
• Matching 401(k) up to 4%
• Flexible Vacation & Paid Time Off
• Short-term Disability and Life Insurance

About the Role

We're looking for a versatile Data Engineer / Data Scientist to join our software engineering team. This hybrid role is perfect for someone who thrives at the intersection of data infrastructure and analytics — designing scalable data pipelines one day and modeling data to generate actionable insights the next.

You'll work across the full data stack, collaborating with engineers, analysts, and product teams to make data accessible, reliable, and impactful.

What You'll Do

• Build and maintain scalable ETL pipelines using AWS Glue, Lambda, and other AWS services
• Design and optimize data lake and data warehouse architectures in AWS
• Work with both relational databases (PostgreSQL, MySQL) and NoSQL databases (DynamoDB, MongoDB)
• Develop and deploy data models, dashboards, and insights to support decision-making
• Collaborate with stakeholders to understand data needs and identify opportunities for improvement
• Ensure data quality, integrity, and observability across our systems
• Automate workflows and contribute to infrastructure-as-code (Terraform, AWS CDK)

Requirements

• 3+ years of experience in a Data Engineering or Data Science role
• Strong experience with AWS services: Glue, Lambda, S3, Athena, Redshift, and CloudWatch
• Solid understanding of ETL concepts and hands-on experience with data pipeline design and orchestration
• Proficiency in SQL, Python, and/or PySpark
• Familiarity with data modeling, schema design, and query optimization
• Experience working with structured and unstructured data
• Comfortable with version control (Git) and CI/CD workflows

Preferred Qualifications

• Experience with machine learning, Apache Airflow, or data visualization tools (QuickSight, Tableau, Looker)
• Background in statistics or machine learning
• Experience working in agile, cross-functional teams
• Knowledge of data security best practices and compliance (HIPAA, HITRUST, SOC2)
• Exposure to DevOps practices and Infrastructure-as-Cod