DataOps Engineer for Drug Discovery Pipelines (Remote)

Arcadia Inc.; Snowflake (AZ); Remote; USD 110,000 - 170,000; Full time

Benefits offered by this job

Possibility to work remotely

Professional growth opportunities

Company laptop

Job summary

Arcadia Inc. seeks a DataOps Engineer to build, maintain, and optimize data pipelines and infrastructure to support drug design and discovery.

The role evolves data models and ensures scientific data is accessible, reliable, and ready for computational research and AI-driven applications. You will design and maintain data models, develop pipelines in Python, and manage data infrastructure across PostgreSQL and Snowflake, improving data quality and enabling scalable analytics in collaboration

Qualifications

• Hands-on data modeling, database design, architecture, and maintenance.
• Strong experience with PostgreSQL, including database structure, SQL queries, and performance optimization.
• Practical experience with Snowflake and modern data warehousing concepts.
• Proficiency in Python for data processing, pipeline development, and automation.
• Understanding of data engineering principles, including data quality, reliability, scalability, and maintainability.
• Ability to troubleshoot data-related issues and collaborate effectively with software engineers, data scientists, and scientific researchers.

Responsibilities

• Design and maintain data models and databases, ensuring reliability and adaptability.
• Build and optimize data pipelines using Python and modern data engineering practices.
• Manage and evolve data infrastructure across PostgreSQL and Snowflake, extending data models for new sources.
• Improve data quality, accessibility, and scalability through validation, monitoring, and collaboration with teams.

Skills

Data modeling

Database design

Architecture

Data quality

Collaboration

Troubleshooting

Tools

PostgreSQL

Snowflake

Python

API design

Docker

Kubernetes

GitOps

AWS

Job description

Arcadia Inc. seeks a DataOps Engineer to build, maintain, and optimize data pipelines and infrastructure to support drug design and discovery.

The role evolves data models and ensures scientific data is accessible, reliable, and ready for computational research and AI-driven applications. You will design and maintain data models, develop pipelines in Python, and manage data infrastructure across PostgreSQL and Snowflake, improving data quality and enabling scalable analytics in collaboration