Database Specialist - Contract

PathAI; Myrtle Point (OR); Remote; USD 80,000 - 120,000; Full time

Job summary

A leading healthcare technology company is seeking a data engineer to optimize storage and improve data management for machine learning applications. This remote role focuses on enhancing ETL pipelines and collaborating with cross-functional teams. Ideal candidates should have a strong background in relational databases, cloud warehousing, and proficiency in Python. Join us to make a significant impact on patient outcomes.

Qualifications

• Proven expertise with relational databases including schema design and query optimization.
• Strong experience with cloud data warehousing solutions.
• Proficiency in Python for application development and data processing.

Responsibilities

• Analyze and optimize storage strategies for machine learning experiment data.
• Design and implement intelligent data retention for large-scale datasets.
• Modernize ETL pipelines for enhanced scalability.

Skills

Relational databases expertise

ETL development

Cloud data warehousing

Big data deployments

Python proficiency

Apache Airflow

Job description

Overview

Contract duration: minimum 6 months. Remote work from anywhere within the U.S. Opportunity to work with cutting-edge technology in machine learning and data infrastructure. Collaborative environment with cross-functional teams. Chance to significantly impact patient outcomes through improved data management.

Responsibilities

• Analyze and optimize storage strategies for machine learning experiment data and metadata.
• Design and implement intelligent retention and expiration for large-scale datasets.
• Modernize and refactor ETL pipelines to enhance scalability and maintenance.
• Build and enhance database-backed applications that support machine learning research and production analytics.
• Collaborate with machine learning engineers, site reliability engineers, and platform teams.

Qualifications

• Proven expertise with relational databases (e.g., Postgres, Amazon RDS, Aurora), including schema design, query optimization, and performance tuning.
• Strong experience with ETL development and cloud data warehousing (e.g., Snowflake, Redshift).
• Familiarity with big data deployments and scalable architectures such as Spark and Hive.
• Experience with Apache Airflow for systems automation.
• Proficiency in Python for application development, data processing, and automation.

Preferred Qualifications

• Background in machine learning data pipelines or analytics-heavy environments.
• Knowledge of data governance, retention policies, or cost-optimization strategies in cloud environments.